Su Lin Lim Thesis (PDF 10MB)

Malnutrition in hospitalised patients and clinical outcomes: A missed opportunity?

MALNUTRITION IN HOSPITALISED PATIENTS AND

CLINICAL OUTCOMES:

A MISSED OPPORTUNITY?

SU LIN LIM

Bachelor of Science in Dietetics (Honours)

Thesis by Publication

submitted for the

Doctor of Philosophy

in the

School of Exercise and Nutritional Sciences

Queensland University of Technology

Australia

January 2014


ABSTRACT

Introduction

Studies have shown that malnutrition is prevalent in hospitals and ranges from

13-78%. Poor nutrition leads to a range of poor clinical and functional outcomes.

Although previous studies have shown a prospective association between

malnutrition and clinical outcomes, the confounding effect of disease and its

complexity using diagnosis-related groups (DRG) has never been taken into

consideration. It is widely agreed that disease and malnutrition are closely linked

and that disease may cause secondary malnutrition and vice-versa. However it is

often argued that length of stay (LOS), mortality and hospitalisation costs are

primarily determined by the patient’s medical condition rather than malnutrition.

In order for malnutrition to be properly addressed, there must be a

comprehensive “start-to-end” system that provides continuity of care from

admission to post-discharge. This should include screening hospitalised patients

to identify those who are malnourished or at risk of malnutrition, referral of

appropriate patients for nutrition assessment, inpatient nutrition intervention and

post-discharge follow-up.

The first critical step in managing malnutrition is the identification of malnourished

patients. Despite the prevalence and consequences of malnutrition these

patients are often not identified, with up to 70% not receiving any nutrition

intervention. All patients admitted to hospital should be systematically screened,

using a nutrition screening tool that is simple, quick, reliable, valid and cost

effective. Although there are many nutrition screening tools, none have yet been

developed and validated in Singapore, since most studies have been within the

Caucasian population. With its multi-ethnic population, the applicability of existing

nutrition screening tools to Singaporean patients is uncertain, especially the

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cutoffs used to identify risk of malnutrition. A screening tool specific for the

Singapore population is needed, and once developed should be validated.

For a nutrition screening tool to be effective, it must be completed fully and

accurately. Studies have reported screening incompletion and error rates of 28-

97%. High levels of missing data were found in commonly used nutrition

screening tools. Failure to achieve accurate and complete nutrition screening will

affect the final score allocated to a patient, which may result in a malnourished or

at risk patient not being referred for nutritional intervention.

To complete the process of nutrition screening, any patient identified at screening

to be malnourished or at risk of malnutrition should be referred to receive a full

nutrition assessment and intervention. This should be followed by a

comprehensive management of malnourished patients, including monitoring

and/or intervention. However, these patients often become lost to follow-up after

discharge. There is limited evidence on methods of follow-up post-discharge from

hospital to effectively treat malnutrition.

Aims The aims of the research programme were to:

i) determine the prevalence of malnutrition on admission to a tertiary

hospital in Singapore and its impact on cost of hospitalisation, length of

stay, readmission and 3-year mortality. ii) develop and validate a new nutrition screening tool for use in the

Singaporean adult population admitted to an acute hospital.

iii) confirm the reliability and validity of the new nutrition screening tool

administered by nurses in a new cohort of patients. iv) investigate the compliance rate of nurses in conducting nutrition screening

and referring at risk patients to the dietitians; and determine the effect of

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quality improvement initiatives in improving the overall performance of

nutrition screening.

v) explore and determine the effectiveness of the current system and an

alternative model on dietetics follow-up rate of malnourished hospital

patients post-discharge.

Methodology

The study programme was conducted in four phases:

i) a cross-sectional 3-year prospective study on 818 newly admitted

patients to determine the prevalence and outcomes of malnutrition,

adjusted for gender, age and ethnicity and matched for Diagnosis-Related

Groups (DRG). The group of patients were also screened using five

parameters that contribute to the risk of malnutrition, resulting in

development and validation of a new nutrition screening tool called 3-

Minute Nutrition Screening (3-MinNS)

ii) a cross-sectional prospective study on 121 patients to confirm the validity

and determine the reliability of 3-MinNS when used by nursing staff, the

intended users of the tool

iii) a 6-year audit and quality improvement study on 4467 patients to improve

nurses’ compliance with 3-MinNS

iv) an audit on dietetic follow-up of 261 malnourished patients discharged

from the hospital in which the results were used to develop a novel model

of care called Ambulatory Nutrition Support (ANS). The effectiveness of

ANS was evaluated via a prospective interventional cohort study on 163

malnourished patients discharged from the hospital.

Results

Using Subjective Global Assessment (SGA), the prevalence of malnutrition was

29%. Malnourished patients had longer hospital stays (6.9 ± 7.3 days vs. 4.6 ±

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5.6 days, p < 0.001) and were more likely to be readmitted within 15 days

(adjusted relative risk = 1.9, 95%CI 1.1–3.2, p = 0.025). Within a DRG, the mean

difference between actual cost of hospitalisation and the average cost for

malnourished patients was three times higher than well-nourished patients (p =

0.014). Mortality was higher in malnourished patients than well-nourished

patients at 1 year (34% vs. 4.1 %), 2 years (42.6% vs. 6.7%) and 3 years (48.5%

vs. 9.9%); p < 0.001. Overall, malnutrition was a significant predictor of mortality

(adjusted hazard ratio = 4.4, 95% CI 3.3-6.0, p < 0.001).

In the development of the new nutrition screening tool (3-MinNS), a combination

of the parameters of weight loss, intake and muscle wastage yielded the largest

area under the curve (AUC) when compared to SGA. The best cutoff point for 3-

MinNS to identify malnourished patients was three (sensitivity 86%, specificity

83%). The subsequent study using nurses to conduct 3-MinNS confirmed the

validity (sensitivity 89%, specificity 88%) and reliability (agreement =78.3%, k=

0.58, p<0.001) of the tool.

After the hospital-wide implementation of nutrition screening, the error rates were

33% and 31% in 2008 and 2009 respectively, with 5% and 8% blank or missing

forms. Of all patients scored to be at risk of malnutrition, 10% were not referred

to a dietitian. With the implementation of a series of quality improvement

initiatives, error rates reduced to 25%, 15%, 7% and 5% in 2010, 2011, 2012 and

2013 respectively; with a reduction in blank or missing forms to 1% for four

consecutive years. Failure to refer appropriate patients to Dietetics decreased to

7% (2010), 4% (2011) and 3% (2012 and 2013).

In the fourth phase, among the malnourished patients seen by dietitians in the

inpatient wards, only 15% of patients returned for follow-up with a dietitian within

four months post-discharge. After implementation of ANS in 2010, the follow-up

rate was 100%. Mean weight improved from 44.0 ± 8.5kg to 46.3 ± 9.6kg

(p<0.001). The Euro Quality of Life - 5 Domain Visual Analogue Scale improved

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from 61.2 ± 19.8 to 71.6 ± 17.4 and handgrip strength from 15.1 ± 7.1 kg force to

17.5 ± 8.5 kg force; p<0.001. Seventy-four percent of patients improved in SGA

score.

Conclusion This research programme is amongst the first to examine the impact of

malnutrition on length of hospital stay, readmission, hospitalisation cost and

mortality in a large sample representative of patients admitted to a major

Singaporean tertiary hospital. It has provided clear evidence that the adverse

outcomes of malnutrition are not just a consequence of the disease process, and

lead to substantial increases in length of hospital stay, readmission rate, mortality

and hospitalisation cost when compared with well-nourished patients of similar

diagnoses and complexities. The research programme led to the development

and validation of a new nutrition screening tool (3-MinNS) and confirms that the

3-MinNS is a valid and reliable nutrition screening tool to be used in Singaporean

acute hospitals. Quality improvement initiatives proved successful in improving

the compliance of nurses to 3-MinNS and ensuring referral of malnourished or ‘at

risk’ patients to dietitians. Finally, this research programme has provided an

evidence-based and effective method for following up malnourished patients

post-discharge, which resulted in improved nutritional status of these patients.

In conclusion, this research programme has successfully delivered a

comprehensive model for managing hospital malnutrition, from screening on

admission and referral for assessment, to intervention and post-discharge follow-

up.

KEYWORDS Malnutrition, Prevalence, Nutrition Screening, Subjective Global Assessment,

Nutrition Intervention, Hospitalisation Outcomes

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TABLE OF CONTENTS ABSTRACT………………………………………………………………………. 1

KEYWORDS……………………………………………………………………… 5

TABLE OF CONTENTS………………………………………………………… 6

LIST OF TABLES……………………………………………………………….. 10

LIST OF FIGURES………………………….……………….….………….…… 11

ABBREVIATIONS……………………….………………..…………………….. 12

PUBLICATIONS RELATED TO THE RESEARCH……..………….………. 14

CONFERENCE ABSTRACTS, POSTERS AND ORAL PRESENTATIONS………………………………………………………………

15

AWARDS ………………………….………………………………..…………… 17

MEDIA INTEREST RELATED TO THE PHD RESEARCH... ……………… 18

SPEAKER AT VARIOUS PLATFORMS RELATED TO TOPIC OF THESIS ………………………………………………………………………….

19

ORIGINALITY OF WORK..……………….……………………………………. 21 ACKNOWLEDGEMENTS……………….……………………………………… 22

BACKGROUND………………………………………………………………….. 23

MODE OF THESIS PRESENTATION………….……………………………... 27

CHAPTER 1: LITERATURE REVIEW……………………………………… 30

1.1 Malnutrition…………….…………………………………………………..

1.1.1 Definitions of Malnutrition………………………………………..

1.1.2 Prevalence of Malnutrition in the Acute Setting ……………....

1.1.3 Risk factors for Malnutrition …………………….………………

1.1.4 Consequences, Clinical Outcomes and Cost of Malnutrition 1.1.5 Potential Confounders for Malnutrition Outcomes ………..….

30

30

34

40

42

56


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1.2 Nutrition Screening…………………………………….…………………

1.2.1 Practical Considerations in Nutrition Screening……...............

1.2.2 Validity of Nutrition Screening Tools……………………………

1.2.3 Reliability of Nutrition Screening Tools…………………………

1.2.4 Reference Standard to Validate a Nutrition Screening Tool…

1.2.5 Compliance with Nutrition Screening…………………………..

60

66

74

78

87

103

1.3 Interventions for Patients with Malnutrition…………………………….

1.3.1 Nutrition Support for Malnourished Patients ………………….

1.3.2 Post-discharged Follow-up of Malnourished Patients………..

1.3.3 Strategies to Improve Post-discharged Follow- up……………

109

111

113

116

1.4 Overall Summary and Gaps in Current Research……………………. 119

1.5 Conceptual Framework of Research Programme……………………. 121

1.6 Research Questions and Objectives…………………………………... 124

1.7 Aims of Research Programme…………………………………………. 126

CHAPTER 2: LINKING THE RESEARCH QUESTIONS ………………….. 127

2.1 Linking the Research Questions and Objectives …………………….. 127

2.2 How the Research Projects are Related ……………………………… 127

2.3 Overview of Research Methodology …………………………………... 130

CHAPTER 3: PREVALENCE OF MALNUTRITION AND ITS IMPACT ON CLINICAL OUTCOMES AND COST ………………………………………….

135

3.1 Introduction ……………………………………………………………….. 135

3.2 Publication: Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality ……………………...

136

3.3 Conclusion…………………………………………………………………. 136

CHAPTER 4: DEVELOPMENT AND VALIDATION OF 3-MINUTE NUTRITION SCREENING TOOL (3-MinNS) …………………………………

145

4.1 Introduction………………………………………………………………... 145

4.2 Publication: Development and validation of 3-Minutes Nutrition Screening (3-MinNS) Tool for acute hospital patients in Singapore…

146

4.3 Conclusion…………………………………………………………………. 147


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CHAPTER 5: VALIDITY AND RELIABILITY OF 3-MINUTE NUTRITION SCREENING ADMINISTERED BY NURSES………………………………...

156

5.1 Introduction…………………………………………………………………. 156

5.2 Publication: Validity and reliability of nutrition screening administered by nurses…………………………………………………………………….

157

5.3 Conclusion………………………………………………………………….. 157

CHAPTER 6: IMPROVING THE PERFORMANCE OF NUTRITION SCREENING……………………………………………………………………...

165

6.1 Introduction…………………………………………………………………. 165

6.2 Publication: Improving the performance of nutrition screening through continuous quality improvement initiatives………………………………

166

6.3 Conclusion………………………………………………………………….. 166

CHAPTER 7: FOLLOW-UP FOR MALNOURISHED POST-DISCHARGED HOSPITAL PATIENTS………………………………………..

191

7.1 Introduction………………………………………………………………… 191

7.2 Publication: A pre-post evaluation of an ambulatory nutrition support service for malnourished patients post hospital discharge: a pilot

study………………………………………………………………………...

192

7.3 Conclusion…………………………………………………………………. 192

CHAPTER 8: DISCUSSION AND RECOMMENDATIONS……....……….. 200

8.1 Overview of Research Questions and Key Findings……………………

8.1.1 Prevalence of malnutrition and outcomes……………………..

8.1.2 Identifying patients at nutrition risk……………………………..

8.1.3 Compliance and referral process of nutrition screening……...

8.1.4 Follow-up of malnourished patients post discharge…………..

200

201

204

209

211

8.2 Recent Developments …………………………………………………….. 215

8.3 Recommendations………………………………………………………….

8.3.1 Clinical practice…………………………………………………..

8.3.2 Education………………………………………………………….

8.3.3 Research…………………………………………………………..

219

219

220

221

8.4 Conclusion and Contribution to Knowledge…………………………… 223


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REFERENCES…………………………………………………………………… 225

APPENDICES…………………………………………………………………… 248

Appendix A: 3-Minute Nutrition Screening………………………………….. 248

Appendix B: Subjective Global Assessment………………………………… 249

Appendix C: 7-Point Subjective Global Assessment……………………….. 250

Appendix D: Euro Quality of Life–5 Domain and Visual Analogue Scale………………………………………………………………

251

Appendix E: Paper on 7-point Subjective Global Assessment ……………

Appendix F: Standard questions and advice given by the dietetics

assistant via telephone follow-up as part of Ambulatory

Nutrition Support Service ……………………………………….

Appendix G: Research Grant…………………………………………………..

253

276

277

Appendix H: Domain Specific Review Board Approval, Singapore………... 279

Appendix I: Human Research Ethics Committee Approval, Queensland

University of Technology………………………………………...

284

Appendix J: Statement of Contribution of Co-Authors…..…………………. 288


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LIST OF TABLES Table 1.0 The amount a patient needs to pay for Dietetics services

with and without government subvention in National

University Hospital, Singapore………………………………..

25

Table 1.1 NHMRC ‘levels of evidence’ for prognostic, diagnostic and

intervention research…………………………………………….

29

Table 1.2 Summary of studies on prevalence of malnutrition in acute

hospitalised patients (multidisciplinary)………………………..

37

Table 1.3 Impact of malnutrition on mortality, length of hospital stay

(LOS), readmission and cost, using different nutritional

assessment/ screening tools and evidence of them being

controlled for confounders………………………………………

50

Table 1.4 Components, strengths and limitations of nutrition screening

tools for hospitalised patients…………………………………..

62

Table 1.5 Nutrition screening tools developed for targeted groups of

people……………………………………………………………..

72

Table 1.6 Reliability and validity of nutrition screening tools in

hospitalised adult patients and method of validation,

including blinding of assessors…………………………………

81

Table 1.7 Comparison of nutrition assessment methods to validate a

nutrition screening tool…………………………………………..

89

Table 1.8 Studies on reliability and validity of Subjective Global

Assessment (SGA) and other modified versions of SGA……

98

Table 1.9 Non-compliance and error rates with various nutrition

screening tools in hospitalised adult patients…………………

107

Table 1.10 Studies on follow-up attendance rate of patients seen by

dietitians…………………………………………………………..

115

Table 2.1 Research questions, objectives and relevant publications….. 129

Table 2.2 Summary of study design, sample size and sampling

strategy……………………………………………………………

130


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LIST OF FIGURES

Figure 1.1 Vicious cycle of the development and progression of

disease-related malnutrition……………………………………..

31

Figure 1.2 Etiology-based malnutrition definitions………………………… 32

Figure 1.3 Prevalence of malnutrition in adult hospitalised patients

(multidisciplinary) differentiated by assessment tools………...

35

Figure 1.4 Risk factors for malnutrition…………………………………….. 41

Figure 1.5 Nutrition Care Process for malnutrition………………………… 110

Figure 1.6 Conceptual Framework for the identification and

management of malnutrition in hospitalised patients….……..

122

Figure 2.1 Schematic diagram on the methodology of research

programme…………………………………………………….

133


ABBREVIATIONS

3-MinNS 3-Minute Nutrition Screening

ADA American Dietetic Association

(Academy of Nutrition and Dietetics)

ANS Ambulatory Nutrition Support

ASPEN American Society for Parenteral and Enteral Nutrition

BCM Body Cell Mass

BIA Bioelectrical Impedance Analysis

BMI Body Mass Index

BOD Burden of Disease

CAMA Corrected arm muscle area

CCI Charlson Comorbidity Index

CIRS Cumulative Illness Rating Scale

CPSS Computerised Patient Support System

DEXA Dual Energy X-Ray Absorptiometry

DMS Dialysis Malnutrition Score

DRG Diagnosis-related groups

DSRB Domain Specific Review Board

E7-SGA Expanded 7-point Subjective Global Assessment

EQ-5D VAS Euro Quality of Life – 5 Domain Visual Analogue Scale

ESPEN The European Society for Clinical Nutrition and Metabolism

ICED Index of Coexisting Disease

IF Impact factor

LOS Length of hospital stay

MAC Mid arm circumference

MAMC Mid arm muscle circumference

MDS Malnutrition Dialysis Score

MNA Mini Nutritional Assessment

MNA-SF Mini Nutritional Assessment – Short Form

MST Malnutrition Screening Tool

MUST Malnutrition Universal Screening Tool

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NPV Negative Predictive Value

NRIa Nutrition Risk Index

NRIb Nutritional Risk Index

NRS Nutrition Risk Score

NRS 2002 Nutritional Risk Screening 2002

NS Non significant

NST Nutrition Screening Tool

NHG National Healthcare Group

NHMRC National Health and Medical Research Council

NUH National University Hospital

NUS National University of Singapore

NUHS National University Health System

PDCA Plan Do Check Action

PG-SGA Patient-Generated Subjective Global Assessment

PPV Positive Predictive Value

QI Quality Initiative

QOL Quality of Life

RCT Randomised Controlled Trial

ROC Receiver Operator Characteristic

RQ Research Question

SGA Subjective Global Assessment

SNAQ Short Nutritional Assessment Questionnaire

SAP System Application Product

TST Triceps Skinfold Thickness

URS Undernutrition Risk Score

VSM Value Stream Mapping

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PUBLICATIONS RELATED TO THE RESEARCH 1. Lim SL, Ong KCB, Chan YH, Loke WC, Ferguson M, Daniels L.

Malnutrition and its impact on cost of hospitalisation, length of stay,

readmission and 3-year mortality. Clinical Nutrition 2012; 31(3):345-350.

(IF = 3.603) (CHAPTER 3) 2. Lim SL, Daniels L. Reply - Malnutrition and its impact on cost of

hospitalisation, length of stay, readmission and 3-year mortality. Clinical

Nutrition 2013; 32(3):489-490. (IF = 3.603) (CHAPTER 3)

3. Lim SL, Tong CY, Ang E, Lee EJC, Loke WC, Chen Y, Ferguson M,

Daniels L. Development and validation of 3-Minutes Nutrition Screening

(3-MinNS) Tool for acute hospital patients in Singapore. Asia Pacific

Journal of Clinical Nutrition 2009; 18(3):395-403. (IF = 1.438). (CHAPTER 4)

4. Lim SL, Ang E, Foo YL, Ng LY, Tong CY, Ferguson M, Daniels L. Validity

and reliability of nutrition screening administered by nurses. Nutrition in

Clinical Practice 2013; 28:730-736. (IF = 1.594). (CHAPTER 5)

5. Lim SL, Ng SC, Lye J, Loke WC, Ferguson M, Daniels L. Improving the

performance of nutrition screening through continuous quality

improvement initiatives. Joint Commission Journal of Quality and Patient

Safety 2014. (In press) (CHAPTER 6)

6. Lim SL, Lin XH, Chan YH, Ferguson M, Daniels L. A pre-post evaluation

of an ambulatory nutrition support service for malnourished patients post

hospital discharge: a pilot study. Annals Academy of Medicine Singapore

2013. 42:507-513. (IF = 1.362). (CHAPTER 7) 7. Lim SL, Lye J, Liang S, Miller M, Chong YS. Development and Validation

of an Expedited 10g Protein Counter (EP-10) for Dietary Protein Intake

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Quantification. Journal of Renal Nutrition 2012; 22(6):558-566. (IF =

1.480) 8. Lim SL. Using Expedited 10g Protein Counter (EP-10) for Meal Planning.

2012; Journal of Renal Nutrition 2012; 22(6):e55. (IF = 1.480) 9. Lim SL, Lye J. Nutritional Intervention Incorporating Expedited 10g

Protein Counter (EP-10) to Improve the Albumin and Transferrin of

Chronic Hemodialysis Patients. International Scholarly Research Network

- Nutrition 2012. Article ID 396570, 5 pages. Doi: 10.5402/2013/396570

10. Ang Emily, Lim HL, Mordiffi SZ, Chan MF, Lim SL. Nutritional risk of

cancer patients receiving chemotherapy in the ambulatory care setting: A

prospective study. Singapore Nursing Journal 2012; 39(4):2-11.

CONFERENCE ABSTRACTS, POSTERS AND ORAL PRESENTATIONS 1. Lim SL, Tong CY, Ang NK, Loke WC, Chen Y, Lee EJC, Ferguson M,

Daniels L. A Simplified Nutrition Screening Tool (3-MinNS) has Good

Correlation with Subjective Global Assessment (SGA). 15th International

Congress of Dietetics, Seoul, Korea, Sept 2008.

2. Lim SL, Tong CY, Seet RCS, Loke WC, Ferguson M, Daniels L.

Validation of Mid Arm Muscle Circumference and Triceps Skinfold

Thickness with Subjective Global Assessment. In: Oh VMS, Yap HK,

editors. Proceedings of the 8th Annual Scientific Congress National

Healthcare Group; 16-17 Oct 2009: Singapore: Annals of the Academy of

Medicine; 2009; 38:S8.

3. Lim SL, Lye J, Liang S, Miller M, Chong YS. Development and Validation

of an Expedited 10g Protein Counter (EP-10) for Dietary Protein Intake

Quantification. In: Tan EK, editor. Proceedings of the Singapore Health

15

http://dx.doi.org/10.5402/2013/396570�


and Biomedical Congress; 11-12 Nov 2011: Singapore: Annals of the

Academy of Medicine; 2011. 40: S41.

4. Lim SL, Ang E, Foo YL, Ng LY, Tong CY, Ferguson M, Daniels L. Validity

and reliability of 3-Minute Nutrition Screening performed by nurses on

Oncology and Surgical patients. 14th Congress of Parenteral and Enteral

Nutrition Society of Asia, Taipei, Taiwan, 14-16 October 2011.

5. Lim SL, Ong KCB, Chan YH, Loke WC, Ferguson M, Daniels L.

Malnutrition and its impact on cost of hospitalisation, length of stay,

readmission and 3-year mortality. In: Tan EK, editor. Proceedings of the

2nd Singapore Health and Biomedical Congress; 11-12 Nov 2011:

Singapore: Annals of the Academy of Medicine; 2011;40:S10.

6. Lim SL, Ang E, Ng SC, Tong CY, Ferguson M, Daniels L. Reducing

incompletion and error rates in nutrition screening. Proceedings of the 3rd

Singapore Health and Biomedical Congress; 28-29 Sept 2012: Singapore:

Annals of the Academy of Medicine; 2012; 41:S194.


of a post-discharge ambulatory nutrition support service for malnourished

patients: a pilot study. Proceedings of the Singapore Health and

Biomedical Congress; 28-29 Sept 2012: Singapore: Annals of the

Academy of Medicine; 2012; 41:S67.


of a post-discharge ambulatory nutrition support service for malnourished

patients: a pilot study. 21st International HPH Conference, Gothenburg,

Sweden, 22-24 May 2013.

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AWARDS Year Awards 2013 Awarded NUHS Outstanding Quality Improvement Award for Multi-year

Project to Improve the Performance of Nutrition Screening Hospital-wide” (the only project accorded “outstanding” status out of 29 projects evaluated)

2013 Awarded Singapore Allied Health Award – 1st Prize Winner for Best

Oral Presentation in Singapore Health and Biomedical Congress for research on “7-point Subjective Global Assessment is more time sensitive than conventional Subjective Global Assessment in detecting nutritional changes”.

2011 Awarded Singapore Allied Health Award – 1st Prize Winner for Best

Oral Presentation in Singapore Health and Biomedical Congress for research on “Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality”.

2011 Awarded National Healthcare Quality Improvement Commendation

Prize for project titled “Reducing the turnaround time from nutrition screening referral of nutritionally at risk patients till being seen by dietitians”.

2011 Awarded Model Allied Health Professional Award 2011 (for Research

Contribution) 2011 Awarded Outstanding Project Award for project titled “Dietetics Referral

by Nurses Using Nutrition screening Score upon Admission”. 2011 Gold Medalist for Singapore Public Service 21 Excellence Award for

best ideas contributed in the area of public service (nutrition screening and management)

2010 Awarded a grant (S$153,000) from the Healthcare Quality Improvement

and Innovation Funds for proposal on “Development of novel approaches to improve the nutritional status of malnourished patients discharged from hospital and evaluation of its effectiveness”.

2009 2nd Runner-up for Best Oral Presentation for research on “Validation of

Mid Arm Muscle Circumference and Triceps Skinfold Thickness with Subjective Global Assessment”

2009 Merit Award for NUHS Way Quality Improvement Project titled “Improving

the Nutritional Status of Patients Discharged to Nursing Home on Tube Feeding”

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Media Interest Related to the PhD Research • Newspaper interview: “More Malnutrition cases detected with NUH

Screening Tool”, TODAY, 11 January 2013. http://www.nuh.com.sg/wbn/slot/u3007/Patients%20and%20Visitors/Newsroom/Media%20Articles/2013/JAN/today_11Jan_more%20malnutrition%20cases%20detected%20with%20NUH%20screening%20tool.pdf

• Newspaper interview: “NUH sees Success in Tackling Patient with

Malnutrition” Strait Times.com, 11 January 2013. http://www.straitstimes.com/breaking-news/singapore/story/nuh-sees-success-tackling-patient-malnutrition-20130111

• Newspaper interview: “Malnutrition Problems” Berita Harian (a Singapore National newspaper in Malay language), 27 February 2013. http://www.nuh.com.sg/wbn/slot/u3007/Patients%20and%20Visitors/Newsroom/Media%20Articles/2013/FEB/270213%20BH%20Pg%2012.pdf

• Health Magazine interview: “Malnutrition and Ageing” EzyHealth, April

Issue, 2013 • National University Hospital Publication: “Beating Malnutrition”, LifeLine,

2012, Issue 1, Page 6. http://www.nuh.com.sg/wbn/slot/u3007/lifeline/Lifeline_1_2012.pdf

• Newspaper interview: “Eating Well in Your Autumn Years”, TODAY, 20

February 2010 http://www.nuh.com.sg/wbn/slot/u2995/mediaarticlesfeb10/TDY_20-21Feb10_Eating_well_in_your_autumn_years.pdf

• Agency of Integrated Care Publication: “3-Minute Nutrition Screening”

Mosaic, October 2011, Issue 7, Page 9 http://www.aic.sg/newsletter/archives/mosAIC/Oct2011/index.html#/10/

18

http://www.nuh.com.sg/wbn/slot/u3007/Patients%20and%20Visitors/Newsroom/Media%20Articles/2013/JAN/today_11Jan_more%20malnutrition%20cases%20detected%20with%20NUH%20screening%20tool.pdf�



http://www.straitstimes.com/breaking-news/singapore/story/nuh-sees-success-tackling-patient-malnutrition-20130111�

http://www.straitstimes.com/breaking-news/singapore/story/nuh-sees-success-tackling-patient-malnutrition-20130111�

http://www.nuh.com.sg/wbn/slot/u3007/Patients%20and%20Visitors/Newsroom/Media%20Articles/2013/FEB/270213%20BH%20Pg%2012.pdf�

http://www.nuh.com.sg/wbn/slot/u3007/Patients%20and%20Visitors/Newsroom/Media%20Articles/2013/FEB/270213%20BH%20Pg%2012.pdf�

http://www.nuh.com.sg/wbn/slot/u3007/lifeline/Lifeline_1_2012.pdf�

http://www.nuh.com.sg/wbn/slot/u2995/mediaarticlesfeb10/TDY_20-21Feb10_Eating_well_in_your_autumn_years.pdf�

http://www.nuh.com.sg/wbn/slot/u2995/mediaarticlesfeb10/TDY_20-21Feb10_Eating_well_in_your_autumn_years.pdf�

http://www.aic.sg/newsletter/archives/mosAIC/Oct2011/index.html#/10/�


SPEAKER AT VARIOUS PLATFORMS RELATED TO TOPIC OF THESIS

DATE TOPICS AUDIENCE

9/6/09 Nutrition Screening New Nurses in National University Hospital (NUH)

14/7/09 Nutrition Screening New Nurses in NUH



27/10/09 Malnutrition cutoffs and validation of upper-arm anthropometrics for Singapore patients NUH Dietitians and students

15/12/09 Nutrition Screening Roadshows NUH Nurses

17/12/09 Nutrition Screening Roadshows NUH Nurses




8/3/10 Nutritional Needs of the Elderly Medical Students Year 2, National University of Singapore

8 & 9/10/10 Nutrition Screening and Assessment

Total Nutrition Therapy Course for Doctors, Nurses, Dietitians in Singapore

22/12/10 3-Minute Nutrition Screening Dietitians & Nurses from University Hospital, Kuala Lumpur, Malaysia


25/1/11 Development and Validation of Expedited 10 g Protein Exchange (EP-10) Dietitians, NUH



25/3/11 3-Minute Nutrition Screening Dietitians & Nurses from Jurong General Hospital

8/4/11 Nutrition Screening and Assessment

Total Nutrition Therapy Course for Community Hospitals and Nursing Homes

28/6/11 Nutrition assessment and Clinical Outcomes of Malnutrition

4th year Medical Students from National University of Singapore

14/4/11 Subjective Global Assessment Dietitians in NUH

13/4/11 3-Minute Nutrition Screening New Nurses in NUH 13/7/11 3-Minute Nutrition Screening New Nurses in NUH

3/8/11 3-Minute Nutrition Screening Nurses from Sree Narayanan Nursing Home

11/8/11 3-Minute Nutrition Screening New Nurses in NUH

19


15/8/11 Importance of Nutrition Screening Nursing Directors from all nursing homes in Singapore





11/11/11 Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality”.

2nd Singapore Health and Biomedical Congress

21/11/11 Nutritional Management of Renal Patient Advanced Diploma in Nursing (Nephrology)

6/1/12 Expedited 10g Protein Counter (EP-10) for Quantification and Recommendation of Dietary Protein Intake

Dietitians in Malaysia (Central Region)

25/1/12 Nutritional Management of Orthopaedic Patient Advanced Diploma in Nursing (Orthopaedics)


25/2/12 Importance of Hospital Malnutrition, Nutrition Screening and Assessment

Gastroenterology Society of Singapore – Nutrition Support Course 2012

17/7/12 Using a novel Expedited 10 g Protein Counter (EP-10) for assessment and meal planning of dialysis patients

Malaysian Dietetics Congress (Dietitians in Malaysia)


24/8/12 Screening and Nutrition Assessment Total Nutrition Therapy Course for Clinicians and Dietitians in Singapore



10/10/12 Malnutrition and Nutrition Management in Surgical patients Surgical Doctors in NUH

5/11/12 Nutritional Requirements and Challenges for the Elderly in Singapore Doctors, Dietitians, Nurses






23/8/13 Screening and Nutrition assessment Total Nutrition Therapy Course for Clinicians and Dietitians in Singapore

20


ORIGINALITY OF WORK The work in this thesis is my original work not submitted elsewhere for a degree

at any other institution of higher education. To the best of my knowledge, this

thesis contains no material previously published or written by another person

except where due reference is made.

Signed: Date: 17 January 2014

21


ACKNOWLEDGEMENTS There are many people to whom I am indebted and the journey to complete my

PhD would not be possible without them.

First and foremost, I would like to thank my supervisors Professor Lynne Daniels

and Dr. Maree Ferguson for their continual support and encouragement.

Professor Lynne Daniels encouraged me to pursue a Masters and later nudged

me to articulate to PhD. I would not have dreamed of doing Masters 6 years ago,

what more a PhD. Lynne, thanks for your continual support, guidance, direction

and your belief in me.

I would like to thank both my supervisors for their expertise, valuable input and

advice on my thesis and publications. If Prof. Daniels provided her wealth of

wisdom and the eagle’s eye view, Dr. Ferguson complemented with her detailed

and meticulous input. I must say that I have the best pair of supervisors I could

ever wish for. I greatly admire their intellect, rigor and dedication.

I would also like to thank my husband Dr. Loke Wai Chiong, whose tremendous

encouragement, love, understanding and support keeps me going when the

journey gets tough. Many times when I had to burn the midnight oil to write my

manuscript for publication or thesis, he would keep me company. My two young

boys were incredibly understanding and somehow understood that their Mama

could not be as available to them during this time.

My gratitude goes also to National University Hospital’s Director of Clinical

Support Services Mr. Dennie Hsu, my boss who supported my scholarship

application; and encouraged and supported me in my journey.

Finally, I would like to acknowledge National Healthcare Group and subsequently

National University Hospital for providing me with a scholarship for my PhD.

22


BACKGROUND

This section outlines the background to the research setting, student and the

Singapore healthcare financing system.

Setting

National University Hospital (NUH), a 987-bed acute tertiary hospital, is one of

the leading hospitals in Singapore with a comprehensive range of medical and

surgical specialties. It has close links with the National University of Singapore

(NUS), which is situated adjacent to the hospital. All study participants recruited

under this research programme are patients of National University Hospital.

Student’s Background

The student, Ms. Su Lin Lim is presently the Senior Assistant Director and Chief

Dietitian of the Dietetics Department at the National University Hospital,

Singapore. She developed a nutrition screening tool in 2002 for National

University Hospital, Singapore. As principal investigator, she was subsequently

awarded a S$45,000 grant from Singapore’s National Healthcare Group to

validate the tool on newly admitted hospitalised patients. After embarking on her

PhD, the tool was refined, with validation of the final version of the tool called 3-

Minute Nutrition Screening (3-MinNS) published in 2009 (Lim et al., 2009),

(Appendix A). The tool is currently being used hospital-wide in National

University Hospital, in other hospitals and nursing homes in Singapore and in

Malaysia. She has since taught over 7000 Singaporean and Malaysian nurses

and dietitians to use the 3-MinNS.

Another focus of her PhD research programme was to examine ways to improve

the outcomes of malnourished hospitalised patients discharged from the hospital.

23


The proposal was awarded funding of $153,000 from the Healthcare Quality

Initiative and Innovative Fund (HQI2F).

Su Lin has received numerous awards for her research and quality improvement

initiatives. She was awarded the National University Health Services Model Allied

Health Award in 2011 for her research contributions. At the national level, she

won the National Healthcare Group (NHG) Best Oral Presentation in 2006, NHG

Young Investigator’s Bronze Award in 2007, Singapore Allied Health Award for

best oral presentation for 3 consecutive years from 2009 to 2011. She was

awarded the Singapore National Day Efficiency Medal in year 2007 and was a

Gold Medalist for Singapore Public Service 21 Excellence Award in 2011.

Singapore Healthcare Financing System

Singapore emphasises personal responsibility in healthcare financing. In general,

acute health care services in Singapore are financed through the individual,

government and/or means testing.

a) Individual • Out-of-pocket payment at the point of consumption – Patient have to pay out

of pocket for almost all medical and other outpatient services including

Dietetics services. Typically, a patient will have to pay S$55 for the 1st

Dietetics Consult and S$30 for a Follow-up Dietetics Consult.

• Medisave – this is a medical savings scheme with emphasis on personal

responsibility. For an employed person, 20% of his/her pay and 14.5% of the

employer’s contribution will go towards Central Provident Fund (CPF) every

month. The Central Provident Fund is a social security savings plan

that provides for Singaporeans in old age. Out of the monthly 34.5%

contribution, 6.5% will go into Medisave, which can be used to pay for

24


inpatient charges when a patient is admitted to hospital. Medisave cannot be

used for outpatient payment.

• Medishield – this is health insurance for catastrophic illness with premiums

payable from Medisave. A person can also subscribe to other insurance

schemes from private insurance companies. A person who has Medishield

can claim insurance for his/her hospitalisation expenses.

b) The Government • The Singapore government provides subventions to subsidise the healthcare

cost of patients in the public sector health services. These subventions are

demonstrated in Table 1.0 for Dietetics services. An estimate of 80% of

patients seen by a dietitian pay the subsidised rate.

Table 1.0: The amount a patient needs to pay for Dietetics services with and without government subvention in National University Hospital, Singapore

Patient Group 1st Dietetics

Intervention

Follow-up Dietetics

Intervention

Private patient (no government subvention) S$ 55 S$ 30

Subsidised patient (with government subvention) S$ 22 S$ 12

• Medifund or social assistance is available for patients who cannot afford to

pay the subsidised rate, following financial assessment by a medical social

worker. Patients who qualify for Medifund will have between 50%-100% of

their already subsidised medical bills paid by the government for both

inpatient and outpatient services. About 5% of Dietetics’ outpatients are

funded by Medifund.

25


c) Means Testing • The Singapore Government recognises that intermediate and long-term

healthcare can be expensive.

• To ensure government subsidies for healthcare services are distributed

appropriately and equitably, an income assessment framework “Means

Testing” was introduced in the year 2000.

• Subsidies are available only to individuals who are Singapore citizens or

permanent residents and are applicable only to government-funded

institutions and services.

• Means Testing takes into consideration gross income of the patient, spouse

and immediate family members, number of family members and ownership of

major assets such as private property.

In summary, healthcare expenses in Singapore are partially borne by the user,

with subsidies available to the majority of patients in a government restructured

hospital. Compulsory medical savings play an important role, and insurance such

as Medishield helps to cover for catastrophic illnesses and large hospitalisation

bills. Medifund provides a second-layer safety net for those who are financially

challenged. However financial support for outpatient care is limited.

26


MODE OF THESIS PRESENTATION

The mode of thesis presentation will be by publication. The thesis contains 5

research papers which have been published in peer-reviewed indexed journals.

All the papers are formatted according to the requirements of the individual

journal. Careful planning and execution of the research programme has been

taken to ensure smooth flow of the papers from one to another as the chapters of

the thesis unfold, which are then linked back to the research questions. In order

to minimise repetition and rework, each chapter other than chapters 1 (literature

review), 2 (linking the research questions) and 8 (discussion and

recommendations), will contain a brief introduction of the respective research

paper, the paper itself and a summary of the chapter. The introduction and

summary in the relevant chapters will serve to connect the research questions

and papers to each other.

27


LITERATURE SEARCH STRATEGY The literature search was undertaken as a selective narrative review to address a

range of questions and identify gaps in the current literature, which would lead to

formulation of research questions for this thesis.

Literature search was conducted for “English only” published or unpublished

scientific papers from 1980 to 2012 using keyword search terms of malnutrition,

prevalence, outcomes, nutrition screening, nutrition assessment, nutrition

intervention, nutrition support, multidisciplinary, hospital and inpatients. Additional

filters were used to narrow the searches to adult age groups. PubMed, Web of

Science and Medline databases were used. Searches were supplemented by

reviews, textbooks and by reviewing the references in the studies found. The

initial search was conducted from 1980 to 2008 to develop the conceptual

framework and research questions. Subsequent searches were conducted using

the same search terms and strategies from 2008 to 2013 to include new

references. To maintain focus and smooth flow of the thesis, article exclusion

criteria were applied on papers which focused on non-hospitalised population,

elderly patients and discipline/disease-specific studies. Studies which were

published subsequent to my research and publications are discussed and

outlined in the discussion chapter.

28


LEVELS OF EVIDENCE The levels of evidence were determined according to the NHMRC (National

Health and Medical Research Council, 2009) criteria for prognostic, diagnostic

and intervention studies (Table 1.1). The main purpose of this was to evaluate

the quality of studies in the context of discussing specific review questions and

identifying gaps in the current evidence.

Table 1.1: NHMRC ‘levels of evidence’ for prognostic, diagnostic and intervention research (National Health and Medical Research Council, 2009) Level Prognosis Diagnostic accuracy Intervention I A systematic review of

level II studies A systematic review of level II studies

A systematic review of level II studies

II A prospective cohort study

A study of test accuracy with: an independent, blinded comparison with a valid reference standard, among consecutive persons with a defined clinical presentation6

A randomised controlled trial

III-1 All or none A study of test accuracy with: an independent, blinded comparison with a valid reference standard, among non-consecutive persons with a defined clinical presentation6

A pseudorandomised controlled trial (i.e. alternate allocation or some other method)

III-2 Analysis of prognostic factors amongst persons in a single arm of a randomised controlled trial

A comparison with reference standard that does not meet the criteria required for Level II and III-1 evidence

A comparative study with concurrent controls: ▪ Non-randomised, experimental

trial9 ▪ Cohort study ▪ Case-control study ▪ Interrupted time series with a control group

III-3 A retrospective cohort study

Diagnostic case-control study A comparative study without concurrent controls: ▪ Historical control study ▪ Two or more single arm study ▪ Interrupted time series without

a parallel control group IV Case series, or cohort

study of persons at different stages of disease

Study of diagnostic yield (no reference standard)

Case series with either post-test or pre-test/post-test outcomes

29


Chapter 1: LITERATURE REVIEW Introduction This chapter includes a literature review on the prevalence of malnutrition, its

risks and consequences, and current practices in nutrition screening for

hospitalised adult patients. This is followed by a review of interventions and

follow-up for patients with malnutrition. The review will identify significant gaps in

the evidence for local malnutrition data and its impact on outcomes, nutrition

screening and interventions, which form the basis of the research questions in

this thesis.

1.1 MALNUTRITION

1.1.1 Definition of Malnutrition

There are several definitions of malnutrition and there is as yet no consensus on

a standard one. Malnutrition can also include overnutrition or obesity (Soeters et

al., 2008), however in this thesis the focus will be on the undernutrition aspect of

malnutrition.

Soeters et al. defined malnutrition as “a subacute or chronic state of nutrition in

which a combination of varying degrees of over- or under-nutrition and

inflammatory activity has led to a change in body composition and diminished

function” (Soeters et al., 2008). In a review paper by Norman et al. (2008), the

definition of malnutrition focused on imbalance between intake (energy, protein

and micronutrients) and requirements as the main cause of malnutrition (Norman

et al., 2008b). However, the authors also described the inflammatory response

as a contributing factor to malnutrition (Norman et al., 2008b). They explained

that malnutrition together with stress-related catabolism caused by inflammation

30


increases the risk for infections, organ dysfunction and impaired healing. These,

as with all other severe acute illnesses, can be a trigger for the inflammatory

response that consequently results in starvation and catabolism, which further

aggravates malnutrition (see Figure 1.1).

Figure 1.1: Vicious cycle of the development and progression of disease-related malnutrition (Norman et al., 2008b)

Reprinted with permission from Elsevier

The European Society for Clinical Nutrition and Metabolism (ESPEN) consensus

report defined malnutrition as “a state resulting from lack of uptake or intake of

nutrition leading to altered body composition (decreased fat free mass and body

cell mass) and diminished function” (Lochs et al., 2006). A similar definition was

proposed by Hoffer and Jeejeebhoy whereby malnutrition was defined as a state

of nutrient insufficiency, as a result of either inadequate nutrient intake or inability

to absorb or use ingested nutrients (Kinosian & Jeejeebhoy, 1995; Jeejeebhoy,

2000; Hoffer, 2001).

An International Committee was constituted to develop a consensus approach to

defining malnutrition syndromes for adults in the clinical setting (Jensen et al.,

31


2009; Jensen et al., 2010; White et al., 2012). Consensus was achieved through

a series of meetings held at the American Society for Parenteral and Enteral

Nutrition (ASPEN) and ESPEN Congresses. It was agreed that an etiology-based

approach, which incorporates the current understanding of the role of

inflammatory response in the development of malnutrition, would be most

appropriate (Jensen et al., 2009; Jensen et al., 2010). The Committee proposed

the following nomenclature for nutrition diagnosis in adults in the clinical practice

setting: 1) "starvation-related malnutrition", when there is chronic starvation

without inflammation, 2) "chronic disease-related malnutrition", when

inflammation is chronic and of mild to moderate degree, and 3) "acute disease or

injury-related malnutrition", when inflammation is acute and of severe degree

(Jensen et al., 2010; White et al., 2012) (Figure 1.2).

Figure 1.2: Etiology-based malnutrition definitions. Originated from Jensen GL and adapted by White JV (Jensen et al., 2009; White et al., 2012)

Reprinted with permission from Elsevier

32


It is likely that screening identifies malnutrition risk with a variety of etiologies

such as nutrient deficiencies, sarcopenia, frailty, cachexia of ageing and cancer

cachexia which will have an impact on treatment and outcomes (Jeejeebhoy,

2012; Vandewoude et al., 2012). Therefore, for patients who have been identified

as at risk via screening, it is important to follow through with a thorough

nutritional and clinical assessment so that the etiology of malnutrition can be

established and a more targeted approach to treatment carried out (Hamerman,

2002; Burton & Sumukadas, 2010; Morley et al., 2010; Theou et al., 2011; Sayer

et al., 2013).

33


1.1.2 Prevalence of Malnutrition in the Acute Setting

Many previous studies have shown that malnutrition is prevalent in hospitals

(McWhirter & Pennington, 1994; Edington et al., 2000; Waitzberg et al., 2001;

Thomas et al., 2002; Gout et al., 2009; Beghetto et al., 2010). Figure 1.3

compares the prevalence of malnutrition in adult hospitalised patients

(multidisciplinary) using different tools. Prevalence rates of malnutrition between

2% and 69% were observed depending on the tools used and the countries

where the studies were conducted (Kelly et al., 2000; Middleton et al., 2001;

Waitzberg et al., 2001; Thomas et al., 2002; Correia & Campos, 2003; Kyle et al.,

2003; Wyszynski et al., 2003; Pirlich et al., 2006; Singh et al., 2006; Beghetto et

al., 2010; Velasco et al., 2011). Table 1.2 provides more details of the studies

with regard to sample size, cutoffs for malnutrition, time of assessment and the

age of the subjects. Different methodologies used in studies make comparison

and determination of the true prevalence of malnutrition difficult (Corish &

Kennedy, 2000; Covinsky et al., 2002; Pirlich et al., 2003; Kubrak & Jensen,

2007; Gomes Beghetto et al., 2011). For example, in Pirlich’s (2003) study, even

when prevalence was studied on the same cohort of patients, results varied

depending on the tool used; 27% using Subjective Global Assessment (SGA),

17% using Arm Muscle Area (AMA) and only 4% using body mass index (BMI).

When the same tool for example SGA, was used in large multicentre studies,

there had been variability in the prevalence amongst studies in different countries

from about 27% in German hospitals (Pirlich et al., 2003) to 50% in Latin

American hospitals (Correia & Campos, 2003). This shows that the prevalence of

malnutrition may vary according to the nutrition assessment tool used as well as

patient characteristics such as disease state, age, ethnic mix, culture, country

and institutional setting. In addition, various studies have used different cutoffs

for malnutrition, which affects the rate of malnutrition. For example, three studies

used different BMI cutoffs for malnutrition: <18.5 kg/m2, <19 kg/m2 and < 20

kg/m2 (Kelly et al., 2000; Thomas et al., 2002; Kyle et al., 2003).

34


Although many studies have been conducted in various countries and contexts,

the use of different tools and cutoff points in these studies limits their

comparability and hence prevents us from truly understanding the prevalence

and scale of the problem globally and in Singapore. Despite the variability in the

tools used, SGA remains the most commonly used nutrition assessment tool to

determine the prevalence of malnutrition in many countries.

At the time prior to this research programme, the “true” prevalence of malnutrition

in a Singapore acute hospital had not yet been established. A study done in Tan

Tock Seng Hospital, an acute hospital in Singapore, found the prevalence to be

14.7% using Subjective Global Assessment (SGA) (Raja et al., 2004). However,

the figure could be higher as the author performed SGA only on patients who

were screened to be at risk of malnutrition with the Malnutrition Screening Tool,

and thus might have missed those who were not detected by the screening tool

(Raja et al., 2004).

Summary of Issues on Prevalence of Malnutrition

In conclusion, there have been studies to measure and confirm the prevalence of

hospital malnutrition in many countries. Evidence of this being a problem is

important to create the appropriate level of awareness that can lead to an action

plan. However there has not been any study on the true prevalence of

malnutrition in Singapore acute hospitals. As Singapore is a developed country,

many healthcare professionals are not convinced that malnutrition exists.

Establishing the prevalence of malnutrition in hospitalised patients in Singapore

is the first-step in understanding whether this is indeed an issue worth

addressing.

35


Figure 1.3: Prevalence of malnutrition in adult hospitalised patients (multidisciplinary) differentiated by nutrition assessment tools*

0

10

20

30

40

50

60

70

80

SGA

MNABMI

AMA

Bioch

emica

lFF

M

Combi

ned

met

hods

Pre

vale

nce

of

mal

nu

trit

ion

(%

)

Singh 2006 (Canada) Braunchweig 2000 (United States)Correia 2003 (Latin America) Wyzynski 2003 (Argentina)Waitzberg 2001 (Brazil)Lazarus 2005 (Australia)Middleton 2001 (Australia)Banks 2010 (Australia)Gout 2009 (Australia)Velasco 2011 (Spain)Pirlich 2006 (Germany)O'Keefe 1986 (South Africa)Barreto Penie 2005 (Cuba)Beghetto 2010 (Brazil)Devoto 2006 (Italy)Thomas 2002 (United States)Kyle 2003 (Switzerland)Kyle 2003 (Germany)Kelly 2000 (United Kingdom)Dzieniszewski 2005 (Poland)McWhirter 1994 (United Kingdom)Edington 2000 (United Kingdom)Meijers 2009 (Netherlands)

SGA = Subjective Global Assessment, MNA = Mini Nutritional Assessment, BMI = Body Mass Index, AMA = Arm muscle area, FFM = Fat free mass, Biochemical = Albumin, prealbumin or total lymphocyte count, Combined methods = Combination of two or more nutritional indicators. *See Table 1.2 for details of study

36


Table 1.2: Summary of studies on prevalence of malnutrition in adult hospitalised patients (multidisciplinary), sorted by nutrition assessment tools

Author, Year N Subjects (Country) Age range (years) Assessment Tool used and Cutoff/

Indicator for Malnutrition

Prevalence of Malnutrition (%) Time of Assessment

(Singh et al., 2006) 69 Inpatients from a general medical ward

(Canada) > 20 yrs (upper range not

specified) SGA: Ratings B & C 69 During hospital stay

(Braunschweig et al., 2000) 404 Inpatients staying > 7 days (United States) > 18 yrs (upper range not

specified) SGA: Ratings B & C Admission: 54 Discharge: 59

Within 72 hours of admission and during discharge

(Correia & Campos, 2003) 9348 Inpatients from hospitals in 13 Latin

America countries (Latin America) > 18 yrs (upper range not


(Wyszynski et al., 2003) 1000 Inpatients from 38 general hospitals

(Argentina) > 18 yrs (upper range not


(Waitzberg et al., 2001) 4000 Inpatients from 25 general hospitals

(Brazil) 18-90 SGA: Ratings B & C 48 During hospital stay

(Lazarus & Hamlyn, 2005) 324 Inpatients in an acute private hospital in

Sydney (Australia) > 18 yrs (upper range not

specified) SGA: Ratings B & C 42.3 During hospital stay

(Middleton et al., 2001) 819 Inpatients in two Sydney teaching

hospitals (Australia) 18-99 SGA: Ratings B & C 36 During hospital stay

(Banks et al., 2007) 2208 Inpatients from 22 acute care facilities in

Queensland (Australia) > 18 yrs (upper range not


(Velasco et al., 2011) 400

Inpatients from internal medicine and surgery departments in three university

hospitals (Spain)

> 18 yrs (upper range not specified)

SGA: Ratings B & C MNA Score < 17

35.3 (SGA) 58.5 (MNA)

Within 36 hours of admission

(Barreto Penie, 2005) 1905 Inpatients from 12 Cuban hospitals

(Cuba) > 19 yrs (upper range not

specified) SGA: Ratings B & C

41 During hospital stay

(Beghetto et al., 2010)

Yr 02 185

Yr 06 1503

Inpatients from a university hospital (Brazil)

Adult (age range not specified)

SGA: Ratings B & C BMI <18.5 kg/m2

Albumin <3.5 g/dL Total Lymphocyte Count < 1.5x103/m3

Year 02 Year 06 39.3 40.2 1.6 5.7 21.3 33.5 63.9 42.2

On admission

SGA = Subjective Global Assessment, PG-SGA = Patient-Generated Subjective Global Assessment, BMI = Body Mass Index, MNA = Mini Nutritional Assessment

37


Table 1.2: Summary of studies on prevalence of malnutrition in adult hospitalised patients (multidisciplinary), sorted by nutrition assessment tools (continued)

Author, Year N Subjects (Country) Age range (years) Assessment Tool used and Cutoff/ Indicator for

Malnutrition Prevalence of

Malnutrition (%) Time of Assessment

(Gout et al., 2009) 275 Inpatients from a public tertiary hospital

(Australia) Not specified SGA: Ratings B & C 23 Within 2 weeks of admission

(Pirlich et al., 2006) 1886 Inpatients from 7 teaching hospitals and

6 community hospitals (Germany) 18-100 SGA: Ratings B & C

BMI <18.5 kg/m2 Arm muscle area < 10th percentile norm value

27.4 (SGA) 4.1 (BMI)

17.1 (AMA)

Same day as hospital admission

(Devoto et al., 2006) 108 Patients admitted to a hospital (Italy) 28-99

SGA: Ratings B & C Prealbumin ≤ 0.17g/L

PINI Score ≥ 1 RBP ≤ 0.03g/L

53 60 64 59

On the 3rd day after admission

(Thomas et al., 2007) 64 Patients admitted to an Acute

Assessment Unit (Australia) > 18 yrs (upper range

not specified)

PG-SGA: Ratings B & C

53 Within 48 hours of

admission

(Thomas et al., 2002) 489 Sub-acute care hospital (United States) 23-102

BMI <19 kg/m2 Albumin <35 g/L MNA Score < 17

18 53 30

During hospital stay

(Kyle et al., 2003) 1760

Patients admitted to 2 hospitals in Geneva and Berlin

(Switzerland & Germany) Not specified

BMI <20 kg/m2

Albumin <35 g/L Fat free mass < 10th percentile of healthy Swiss subjects

Geneva Berlin 17.3 8.5 14.9 11.2

31 17 Within 24 hours of

admission

(Kelly et al., 2000) 219 Patients admitted to a tertiary hospital

(United Kingdom) 18-94 BMI <18.5 kg/m2

9 Within 24 hours of admission

(Dzieniszewski et al., 2005) 3310 Patients admitted to 4 teaching

hospitals (Poland) 16-100 BMI <20 kg/m2

Albumin <3.5 g/dL Total Lymphocyte Count < 1.5x103/m3

10 21 21

On the 1st day of admission

(O'Keefe et al., 1986) 700 Patients admitted medical and surgical

wards (South Africa) Adult (age range not

specified)

Body weight below 20% of ideal weight Fat stores less than 60% of standard

Arm muscle circumference and area less than 80% of ideal

20 30 15 Not specified

SGA = Subjective Global Assessment, PG-SGA = Patient-Generated Subjective Global Assessment, BMI = Body Mass Index, AMA = Arm Muscle Area, MNA = Mini Nutritional Assessment,

TST = Triceps Skinfold Thickness, MAMC = Mid arm Muscle Circumference, PINI = Prognostic Inflammatory and Nutritional Index, RBP = Retinol binding protein

38


Table 1.2: Summary of studies on prevalence of malnutrition in adult hospitalised patients (multidisciplinary), sorted by nutrition assessment tools (continued)

Author, Year N Subjects (Country) Age range (years) Assessment Tool used and Cutoff/ Indicator for

Malnutrition Prevalence of

Malnutrition (%) Time of Assessment

(McWhirter & Pennington,

1994) 500 Patients admitted to a tertiary hospital

(United Kingdom) Not specified Combined method

BMI < 20 kg/m2 with either TST or MAMC below the 15th percentile

40 Not specified

(Edington et al., 2000) 850 Patients admitted to 4 hospitals in

England (United Kingdom) > 18 yrs (upper range

not specified)

Combined method BMI < 20 kg/m2 with either

TST or MAMC below the 15th percentile 20 Within 48 hours of

admission

(Meijers et al., 2009)

8220 to 11036

Patients admitted to 57 hospitals (year 2004) and 49 hospitals (year 2007)

(Netherlands)

> 18 yrs (upper range not specified)

Combined method 1) BMI ≤ 18.5 (age 18–65 y) or ≤20 (age > 65 y); or

2) Unintentional weight loss (≥ 6 kg in the last 6 months or ≥3 kg in the last month); or

3) No nutritional intake for 3 days or reduced intake for >10 days combined with a BMI of 18.5–20 (age 18–65 y) or 20–

23 (age >65 y)

Year 2004: 27 Year 2007: 22 During hospital stay

TST = Triceps Skinfold Thickness, MAMC = Mid arm Muscle Circumference, BMI = Body Mass Index

39


1.1.3 Risk Factors for Malnutrition

The risk factors for malnutrition include pathological factors, socioeconomic

status, and poor awareness of importance of nutrition or adverse hospitalisation

outcomes (Norman et al., 2008b). Medical conditions can contribute to

malnutrition, mediated by inflammatory processes, increased requirements,

appetite suppression, poor absorption of nutrients or mechanical obstructions

(Campbell, 1999; Norman et al., 2008b; Soeters et al., 2008; Jensen et al., 2010).

Socioeconomic factors such as poor income, lack of family support and isolation

are also risk factors for malnutrition (Pirlich et al., 2005). Lack of awareness on

the part of patients as well as healthcare workers is common, including poor

recognition of malnutrition and monitoring of nutritional status. This can lead to

inaction to prevent or treat early signs of malnutrition (Pennington & McWhirter,

1997). For patients who are frequently admitted to hospital, this situation is further

aggravated by hospital routines which often require a “nil by mouth” order, or

adverse conditions arising from hospitalisation such as hospital-acquired infection,

poor appetite, side effects of treatment, depression, missed meals due to

procedures, lack of food choices and inadequate feeding assistance (Butterworth,

1994; Incalzi et al., 1996; Sullivan et al., 1999; Weekes et al., 2009). In a review

paper, Kubrak and Jensen grouped factors contributing to malnutrition into two

main categories: personal and organisational (Kubrak & Jensen, 2007). Personal

factors included disease, age, response to treatment, physical, psychological,

social and financial status (Kubrak & Jensen, 2007). Organisational factors

associated with malnutrition included lack of nutrition screening and

documentation, inadequate training of staff, confusion regarding nutritional

responsibility, increased nursing and dietetics workload and lack of adequate

nutritional intake in the hospital (Kubrak & Jensen, 2007). Kubrak and Jensen’s

broad categorisation into personal and organisational factors is useful, and can in

fact be expanded and sub-categorised further. For example, personal factors can

be further divided into effects of ageing, health (or disease), and social factors.

These are summarised and presented in Figure 1.4.

40


Figure 1.4: Risk factors for malnutrition

Adapted and expanded from Kubrak & Jensen, 2007

by Lim Su Lin, 2012

HEALTH • Cognitive Impairment • Depression • Infection, pressure ulcers • Catabolic state secondary to disease • Nausea and vomiting • Malabsorption/

constipation/diarrhoea • Side effects of treatments i.e.

radiation, chemotherapy • Side effects of medications

SOCIAL • Poor caregiver competency/resources • Cultural/religious factors • Lack of family support • Poor eating habits • Low income • Poor understanding of nutrition • Low literacy level • Poor self-help skills

Risk factors

for malnutrition

HOSPITAL • Nil by mouth, multiple tests • Uninteresting hospital food • Lack of access to food • Repeated admissions to hospital • Restrictive diet • Lack of nutrition screening • Non-compliance to screening • Inadequate training of staff • High workload • Inadequate monitoring • Lack of follow-up post-discharge • Failure to recognise malnutrition

(b) Personal

(a) Organisational

EFFECTS OF AGING • Decreased smell / sensation • Early satiety • Disinterest in food

41


1.1.4 Consequences, Clinical Outcomes and Cost of Malnutrition

Malnutrition leads to a range of poor clinical outcomes (Braunschweig et al., 2000;

Middleton et al., 2001; Correia & Waitzberg, 2003; Norman et al., 2008b; Charlton

et al., 2012). Table 1.3 presents the impact of malnutrition on mortality, length of

hospital stay, readmission and cost, using different nutrition assessment tools.

Most clinical outcome studies are on the Caucasian population and none have

been done on the Asian population (Table 1.3). Non-Caucasian populations may

show different results due to ethnic differences in genetics, lifestyle, behaviours,

exposures to risk factors, perceptions and values. It is important to know the

impact of malnutrition on the clinical outcomes of patients in different healthcare

settings and populations. Consequences of malnutrition on a wide range of

outcomes are discussed further in the following sections.

Length of Hospital Stay

Malnourished patients stay in hospitals 1.5 to 1.7 times longer than well-nourished

patients (Middleton et al., 2001; Correia & Waitzberg, 2003; Planas et al., 2004;

Kagansky et al., 2005). Possible reasons for malnourished patients longer

hospital stay are closely associated with functional status (Cereda et al., 2008a),

cognitive function (Lang et al., 2006), socioeconomic factors (Aliabadi et al., 2008)

and complications such as infection (Correia & Campos, 2003) and pressure

ulcers (Banks et al., 2010a; Banks et al., 2010b). McWhirter & Pennington

showed that 80% of malnourished patients who did not receive any nutritional

intervention experienced further deterioration in nutritional status in the seven

days following admission (McWhirter & Pennington, 1994).

Readmission to Hospital Malnourished patients are twice as likely to be readmitted to hospital compared to

well-nourished patients (Planas et al., 2004). In Planas (2004) study, when

42


patients were classified using SGA, there were more total and non-elective

readmissions over the next 6 months in patients with malnutrition (30%) than in

patients without malnutrition (15%). When anthropometric measurements (BMI

and upper arm anthropometry) were used, there were more total readmissions in

the malnourished group, although no significant differences were observed with

the non-elective readmission rate.

Cost

The longer length of hospital stay for malnourished patients is associated with

greater healthcare costs (Braunschweig et al., 2000; Correia & Waitzberg, 2003;

Planas et al., 2004). Malnutrition also results in increased use of hospital

resources (Correia & Waitzberg, 2003), secondary to higher rates of re-

admissions (Planas et al., 2004), increased infection (Braunschweig et al., 2000;

Rypkema et al., 2004), pressure ulcer and poor wound healing (Banks et al.,

2010a; Banks et al., 2010b; Iizaka et al., 2010). As shown by Correia & Waitzberg

(2003), a malnourished patient costs on average 1.7 times more than a well-

nourished patient (US$228 per day vs. US$138 per day) (Correia & Waitzberg,

2003). This represented an increased cost of 60% for malnutrition. When the cost

of medications and tests were added using respiratory patients for comparison,

the costs of malnourished patients increased up to 310% (Correia & Waitzberg,

2003).

Braunschweig et al. (2000) studied 414 inpatients who stayed in hospital for more

than 7 days in an acute care university hospital in the United States. The study

showed that patients who declined nutritionally, regardless of nutritional status on

admission, had significantly higher hospital charges, which was 1.6 times higher

than patients who did not have any decline in nutritional status (Braunschweig et

al., 2000). Banks et al. (2010) conducted random re-samples of 1000 subjects

extrapolated from statistical models to predict the number of pressure ulcer cases,

associated bed days lost and the economic losses in public hospitals in Australia.

43


The model predicted a mean 16,060 bed days lost caused by pressure ulcer

attributable to malnutrition, which equates to AU$12,968,668 in the two-year study

in public hospitals in Queensland, Australia (Banks et al., 2010b). In a recent

study by Freijer et al. (2013), the additional costs of managing adult patients with

disease-related malnutrition were £1.9 billion in 2011, which equates to 2.1% of

national health expenditure in Netherlands (Freijer et al., 2013).

There are potentially enormous cost savings in addressing hospital malnutrition.

One hospital developed a comprehensive nutrition intervention program that

resulted in savings of $2.4 million over a 2-year period due to decreased LOS

(Brugler et al., 1999). The programme consisted of implementation of a nutrition

screening and malnutrition clinical pathway, organised into four stages which

outlined the progression and timing of care, identification of the patient at high risk

of malnutrition, nutrition care decisions, treatment process during hospitalisation

and discharge planning. The savings were estimated at $1,000 for each patient at

high risk of malnutrition (Brugler et al., 1999).

The cost benefit of extending nutrition services to the home is potentially through

shorter length of hospital stay or reduced hospital readmission. Most studies on

the economic benefit of home nutrition services focus on home parenteral nutrition

(HPN) (Baxter et al., 2005; Marshall et al., 2005). A retrospective cohort study of

29 HPN patients reported monthly savings of US$4,860 per patient in comparison

to the patient receiving parenteral nutrition in the hospital (Marshall et al., 2005).

In another retrospective controlled paired study on 56 digestive surgery patients,

the benefits of nutrition therapy (enteral and parenteral) were compared between

a home-hospital model and a traditional hospital model. The patients from the

home-hospital model achieved the same nutritional benefits as those in the

control group, but with expenses 3 times lower (Brazil Reals (R)$3237 vs.

R$8647; p <0.05). The home-hospital model resulted in economic benefit to the

institution, mainly from the avoidance of hospitalisation and the optimisation in the

usage of hospital beds (Baxter et al., 2005). In preventing unnecessary

44


hospitalisation, beyond savings to the hospital, the patient is also spared the

inconvenience, emotional stress, and time and financial costs of hospitalisation.

Functional Status

Functional status represents patients’ ability to perform activities of daily living

such as bathing, changing, self-feeding, shopping and cooking. Functional status

is usually determined either by interviewing patients using a questionnaire such as

the Barthel Index (Mahoney & Barthel, 1965) or using equipment such as the

handgrip dynamometer (Hunt et al., 1985b). The Barthel Index has been widely

used by physiotherapists and occupational therapists to measure disability and to

evaluate changes in activities of daily living (ADL) function over time especially

during post-stroke therapy (Law & Letts, 1989). The Barthel Index evaluates 10

items related to functional status i.e. bowels, bladder, grooming, toilet use,

feeding, transfer, mobility, dressing, stairs and bathing (Mahoney & Barthel, 1965;

Collin et al., 1988). The total score ranges from 0-20, with lower scores indicating

increased disability (Mahoney & Barthel, 1965).

A simpler method to measure functional status is the hand grip strength which has

gained popularity as a simple, non-invasive measure of muscle strength of upper

extremities and can easily be used in the clinical setting (Norman et al., 2011).

Impaired muscle strength is known to occur in disease-related malnutrition.

Prolonged decreases in nutritional intake lead to loss of body protein from muscle

mass, which in turn results in decreased muscle strength, loss of physical

functionality and poor recovery from illness (Norman et al., 2006). Among all the

methods for measuring functional status, handgrip strength has been the most

commonly used and has been shown to have an inverse association with

malnutrition, and therefore is often used as a good proxy for measuring functional

status (Turnbull & Sinclair, 2002; Thomas et al., 2005; Matos et al., 2007; Norman

et al., 2011). Malnourished hospitalised patients had 25.8% lower hand grip

strength values than well-nourished patients (Norman et al., 2011). In a recent

45


study on 217 patients, it was found that handgrip strength was significantly

correlated with nutritional status using PG-SGA (r = 0.292, p < 0.01). In the same

study, a change in handgrip measurement was an independent predictor of a

change in PG-SGA score (p = 0.04) (Flood et al., 2013). Hence, it is not surprising

that handgrip strength is commonly used as one of the outcome measures for

nutrition intervention in malnourished patients (Paton et al., 2004; Ha et al., 2010;

Norman et al., 2011). For example, Paton et al (2004) found a significant increase

in hand grip strength in malnourished tuberculosis patients after six weeks of

intervention with nutritional supplements when compared to a control group (n=

36, 2.79 ± 3.11 versus. -0.65 ± 4.88, p=0.016) (Paton et al., 2004). A study by Ha

et al. (2010) also found a significant increase in handgrip strength (n = 124,

p=0.002) in stroke patients provided with individualised nutrition support for 3

months compared with a control group (Ha et al., 2010).

Although studies have linked poor handgrip to malnutrition and there is a

suggestion to use it to detect malnutrition or risk of malnutrition (Flood et al.,

2013), handgrip strength cannot be used as a sole marker of malnutrition.

Malnutrition can cause poor handgrip strength but poor handgrip strength may not

necessarily indicate malnutrition, as in the case of stroke or trauma patients. A

recent study found low positive predictive value and specificity when handgrip

strength is used to diagnose malnutrition (positive predictive value = 13%)

(Haverkort et al., 2012). Another limitation of using handgrip strength is that there

are patients who will not be able to grip the dynamometer, for example the

critically ill, stroke patients and patients with severe arthritis of their hands. If

handgrip strength is used to monitor malnourished patients, it should be carried

out together with another established nutrition assessment method e.g. SGA.

Quality of Life

Malnutrition leads to decline in functional status which in turn leads to decreased

quality of life (Norman et al., 2006). There are not many studies examining the

46


direct impact of malnutrition on quality of life (QOL). The few studies showing a

relationship between malnutrition and QOL are disease specific (Norman et al.,

2006) or limited to geriatric populations (Neumann et al., 2005; Rasheed &

Woods, 2013b). In a study on 200 patients with benign gastrointestinal disease,

quality of life was measured using the Medical Outcomes Study 36-item Short-

Form General Health Survey (SF 36) (Ware & Sherbourne, 1992), and found to

be reduced in patients who were classified as malnourished using SGA (Norman

et al., 2006). In this study, malnourished patients suffered significantly impaired

QOL in both the mental and physical domains.

In another study on 133 older adults in rehabilitation, malnourished subjects or

those at risk of malnutrition had poorer QOL than those well-nourished or not at

risk of malnutrition (17 ± 5 versus 19 ± 5, p = 0.008) (Neumann et al., 2005). A

systematic review by Rasheed et al. showed that elderly with malnutrition were

almost three times more likely to experience poor QOL than those who were well

nourished (Odds ratio: 2.85; 95% CI: 2.20-3.70, p<0.001) (Rasheed & Woods,

2013b). As malnutrition leads to poor QOL, improving the nutritional status of

malnourished patients should result in better QOL (Ravasco et al., 2005a;

Ravasco et al., 2005b; Norman et al., 2008a; Rufenacht et al., 2010; Rasheed &

Woods, 2013b).

Pressure Ulcer, Infection and Other Complications

Malnutrition increases the risk of developing infection and pressure ulcers

(Davalos et al., 1996; Banks et al., 2010a). Malnourished patients had at least

twice the odds ratio of having a pressure ulcer compared to well-nourished

patients in public healthcare facilities in Queensland, Australia (Banks et al.,

2010a). This multicenter, cross-sectional audit of 2208 acute and 839 aged care

subjects found that subjects with malnutrition had adjusted odds ratios of 2.6 of

having a pressure ulcer in acute care facilities and 2.0 for residential aged care

facilities. There was also an increased odds ratio of having a pressure ulcer, and

47


having a more severe pressure ulcer (a higher number and/or higher stage

pressure ulcer) with increased severity of malnutrition (Banks et al., 2010a). In

another study of 104 patients admitted for acute stroke, malnourished patients

were more susceptible to urinary tract or respiratory infections (50% versus 24%,

p=.0017) and bedsores (17% versus 4%, p=0.054) than well-nourished patients

(Davalos et al., 1996).

A complication is defined as a condition (disease or accident) which occurs during

hospitalisation in addition to an existing illness (Naber et al., 1997). Pressure

ulcers and infections can be considered complications of hospitalisation if the

patient was not originally admitted with these conditions (iatrogenic conditions).

Complications can be grouped under infectious (such as pneumonia, septicaemia,

wound infection, cystitis) or non-infectious complications (such as intestinal

bleeding, kidney failure, dehydration) (Naber et al., 1997). Two studies have

reported higher complications among patients who were malnourished as

measured by SGA at admission compared to well-nourished patients (Naber et

al., 1997; Braunschweig et al., 2000). Naber et al found a 3-fold increased risk of

infection and all complications in malnourished patients when compared to well-

nourished patients (Naber et al., 1997). Similarly, Braunschweig et al found a 1.4

and 1.8 times increased risk of complications in moderately and severely

malnourished newly admitted patients, respectively (Braunschweig et al., 2000).

In addition, patients who had a decline in nutritional status whilst hospitalised

experienced more complications than those who did not (Braunschweig et al.,

2000). The author suggested that clinicians should focus on reducing declines in

patients' nutritional status as a priority regardless of patients' nutritional status on

admission (Braunschweig et al., 2004).

48


Mortality

Besides increased risk of morbidity and cost, hospitalised patients with poor

nutritional status face an increased risk of mortality (Middleton et al., 2001;

Correia & Waitzberg, 2003; Kagansky et al., 2005). Studies have shown that

patients with malnutrition have a 1.6-1.9 relative risk of death when compared to

well-nourished inpatients (Middleton et al., 2001; Correia & Waitzberg, 2003;

Kagansky et al., 2005). There has only been one study to prospectively

investigate mortality outcomes of malnutrition using data from national death

registers (Middleton et al., 2001). This Australian study revealed that mortality at

12 months was 29.7% in malnourished subjects compared with 10.1% in well-

nourished subjects (p<0.0005) (Middleton et al., 2001). The mortality data was

obtained either from hospital records or from the New South Wales Registry of

Births Deaths & Marriages by requesting a copy of death certificates for all

subjects involved in the study whose survival status was unknown (Middleton et

al., 2001). Obtaining mortality data from the national death registry is an accurate

way to ensure information is captured on subjects who have passed away after

being discharged from the hospital.

So far, all the studies which have found a relationship between malnutrition and

increased mortality in adult patients did not control for illness and other

confounders except for Correia & Waitzberg’s study which took into account the

presence of infection, cancer and age (Correia & Waitzberg, 2003). This will be

discussed in the next section.

49


Table 1.3: Impact of malnutrition on mortality, length of hospital stay (LOS), readmission and cost, using different nutrition assessment tools and evidence of them being controlled for confounders

Author, year

Participants, Country and

Type of Study

Assessment Tool and


Time of Assessment

and Administrator

n Prognostic Indicators

Controlled for confounders

Duration of outcomes tracking

Mortality /Survival LOS Readmission Cost

SUBJECTIVE GLOBAL ASSESSMENT

(Correia & Waitzberg,

2003)

Adult inpatients

randomly selected from 25

Brazilian Hospital, Brazil, Retrospective Cohort Study

SGA: Ratings B & C

Within 72 hours of

admission, administrator not specified

709

Survival in hospital:

Malnourished: 212 (87.6%)

Well nourished: 444 (95.3%)

Malnourished: 16.7 + 24.5

days, median of 9 days, Well

nourished: 10.1 + 11.7 days, median of 6

days

Not Specified

Well- nourished: US$138.00 per patient

Malnourished: US$228.00 per patient (Increase of

60.5%)

Presence of cancer and

infection, age over 60 years

and those undergoing

clinical treatment

During hospital

admission

(Middleton et al., 2001)

Inpatients in two Sydney teaching

hospitals, Australia,

Prospective Study

SGA: Ratings B & C

During hospital stay, administrator not specified

819

Mortality at 12 months:

Malnourished = 29.7%

Well nourished = 10.1%,

Malnourished: Median LOS = 17 days, Well

nourished: Median LOS =

11 days (p<0.0005)

Not Specified Not Specified Not Specified 1 year

(Bauer et al., 2002)

Adult patients with cancer

admitted to an acute care hospital, Australia,

Prospective Study

SGA: Ratings B & C Not Specified 71

Difference in mortality within

30 days of discharge,

between SGA groups (p=0.305

= NS)

Malnourished: Median LOS =

13 days Well nourished: Median LOS =

7 days (p=0.024)

Within 30 days of discharge: SGA C: 17%, SGA B: 52% SGA A: 59% (p= 0.037)

Not Specified Not Specified 1 month

(Gupta et al., 2005)

Colorectal cancer patients (Stages III & IV), United States, Retrospective Epidemiologic

Study

SGA: Ratings B & C

During consultation

with a dietitian,

administrator not specified

234

Median Survival SGA C: 6 mths SGA B: 8.8 mths

SGA A: 12.8 mths

Not Specified Not Specified Not Specified Not Specified 74 months

SGA = Subjective Global Assessment, LOS = Length of hospital stay, mths = months

50


Table 1.3: Impact of malnutrition on mortality, length of hospital stay (LOS), readmission and cost, using different nutrition assessment tools and evidence of them being controlled for confounders (continued)

Lead Author Participants, Country and

Type of Study

Assessment Tool and


Time of Assessment

and Administrator

n Prognostic Indicators Controlled

for confounders

Duration of

outcomes tracking


SUBJECTIVE GLOBAL ASSESSMENT (continued)

(Planas et al., 2004)

Hospitalised patients to a university

hospital, Spain,

Prospective study

SGA: Ratings B & C

Within 48 hours of admission by a single dietitian

400 Not Specified

Undernutrition: 7.5 + 5.4 days, Normonutrition: 5.0 + 5.1 days

(p<0.05)

Readmission over 6 months: Undernutrition

30% vs. Normonutrition 15% (p < 0.05)

Not Specified Not Specified 6 months

(Fiaccadori et al., 1999)

Inpatients with Acute Renal Failure,

Italy, Prospective study

SGA: Ratings B & C

Time of assessment not specified. SGA assessed by 2

trained administrators

309

In-hospital mortality

SGA C: 62% SGA B: 20% SGA A: 18%

SGA C: 34.8 ± 27.7 days

SGA B: 35.1 ± 29.9 days

SGA A: 23.5 ± 14.6 days

p< 0.01)

Not Specified Not Specified Not specified

30 days post

discharge

(Stephenson et al., 2001)

Preoperative liver transplant patients,

United States, Retrospective study

SGA: Mild,

Moderate or

Severe Malnutri

tion

At the time of transplantation

by a single observer

99

60-day or perioperative

mortality

SGA Severe: = 15.6%

SGA Mild to moderate:

3.0% (p = 0.10)

Postoperative LOS SGA Severe: 16 ± 9 days

SGA Moderate: 10 ± 5 days, (p = 0.0027);

SGA Mild: 9 ± 8 days, (p = 0.0006)

Not Specified Not Specified Not specified 60 days

(Gout et al., 2009)

Hospitalised patients admitted < 2 weeks

to a university hospital, Australia,

Retrospective Study

SGA: Ratings B & C

Not specified 275 Not specified

Malnourished: 13.3 ± 10.5 days Well-nourished 8.8 ± 8.8 days

(p< 0.05)

Not Specified Not Specified Not specified During

admission

SGA = Subjective Global Assessment, LOS = Length of hospital stay

51



Lead Author

Participants, Country and Type

of Study

Assessment Tool and


Time of Assessment

and Administrator


for confounders



SUBJECTIVE GLOBAL ASSESSMENT (Modified versions)

(Churchill et al., 1996)

Patients commencing continuous peritoneal

dialysis in 14 centers in Canada

and United States,

Prospective study

7-point SGA: Ratings 1 to

5

At the commenceme

nt of peritoneal dialysis,


680

A 1 unit lower SGA score

was associated with a 25%

increase in the RR of death

7-point SGA Malnourished: 96

days Well nourished:

13 days

Not Specified Not Specified Not Specified Up to 2

years

(Martineau

et al., 2005)

Patients admitted to an Acute Stroke

Unit, Australia,

Prospective study

PG-SGA: Ratings B &

C

Within 48 hours of

admission, administrator was a single

dietitian

73

Inpatient mortality:

Malnourished = 14%,

Well nourished = 2%

(p <0.092, NS)

Malnourished = 8 days,

Well nourished = 3 days

(p <0.001)

Not specified Not specified Not specified During

admission

(Thomas

et al., 2007)

Patients admitted to an Acute

Assessment Unit, Australia,

Prospective study

PG-SGA: Ratings B &

C

Within 48 hours of

admission, administrators

were 2 dietitians

64 Not specified

Malnourished = 5 days,

Well nourished = 4 days (p =NS)

Not Specified Not Specified Not Specified During

admission

PG-SGA = Patient-Generated Subjective Global Assessment, LOS = Length of hospital stay, NS = Non significant

52



Lead Author


Type of Study

Assessment Tool and


Time of Assessment

and Administrator





MINI NUTRITIONAL ASSESSMENT

(Kagansky et al., 2005)

Hospitalised elderly patients aged > 75 years

old in geriatric unit, Israel,

Prospective study

MNA: At risk score = 17-23.5,

Malnourished < 17

Time and administrator not specified

414

Inpatient mortality:

Malnourished = 38.7%,

Well nourished =

12.5% (p < 0.001)

LOS during the 2.7 years:

Malnourished = 59.9 ± 77.0 days, Well nourished = 28.3 ± 27.6

days (p < 0.001)

Not Specified Not Specified Not Specified 2.7 years

(Charlton

et al., 2012)

Hospitalised elderly patients (>65 years old)

admitted to 2 subacute hospitals,

Australia, Retrospective

Study

MNA: At risk score = 17-23.5

Malnourished score < 17)

Within 72 hours of

admission, 476

Mortality hazard rate =

3.41 (p = 0.038)

Median LOS during the 1.5

years: Malnourished = 34 days, At risk

= 26 days Well nourished

= 20 days (p < 0.001)

Number of hospital

readmissions was not

associated with MNA

score (r = -0.004, p = 0.45)

Not Specified

Major Disease Classification at admission,

age, sex, mobility and

LOS at index

admission

12 – 26 months

ANTHROPOMETRY

(Martineau et al., 2005)

Patients admitted to an

acute stroke unit, Australia,

Prospective study

BMI: Cutoff

not specified

Within 48 hours of

admission by a single dietitian

73 Not specified

BMI not a significant

predictor of LOS

Not specified Not Specified Not Specified During admission

MNA = Mini Nutritional Assessment, LOS = Length of hospital stay, BMI = Body Mass Index, NS = Non significant

53



Lead Author


Type of Study

Assessment Tool and


Time of Assessment

and Administrator



Duration of

outcomes tracking Mortality /Survival LOS Readmission Cost

ANTHROPOMETRY (continued)

(Gariballa & Forster,

2007)

Hospitalised patients aged ≥

65 years old. United Kingdom,

Prospective Study

MAC (cutoff for

malnutrition not specified)

During hospitalization


445

Mean MAC = 28.4cm (alive) vs. 26.2cm

(dead).

Not Specified Not Specified Not Specified

Chronic disease, age, drugs, functional

capacity and acute-phase

response

1 year

(Neumann et al., 2005)

Older adults in rehabilitation unit,

Australia, Prospective Study

CAMA: Males < 21.4 cm2, females < 21.6 cm2

Within 4 days of admission, administrator was 1 staff

nurse

133 adults > 65 years

Not Specified

At risk: 15 days, Not at risk: 15 days

(p = NS)

Not Specified Not Specified

Assessment of Quality of Life on

admission

During admission (for LOS)

(Miller et al., 2002)

Older adults in the community, Australia,

Prospective study

CAMA: Males < 21.4 cm2, females < 21.6 cm2

Upon enrollment,

administrators were trained observers

1799 adults > 70 years

Mortality at 8 years: Malnourished: HR =

1.94 Well nourished HR =

1.00 (p = 0.003) Not Specified Not Specified Not

Specified

Age, gender, marital status, smoking, self-rated health,

activities of daily living,

comorbidity, cognition,

depression

8 years

Body Mass Index: < 20

kg/m2

Mortality at 8 years: Malnourished: HR =

1.36 Well nourished: HR =

1.00 (p = NS)

(Planas et al., 2004)

Hospitalised patients to a

university hospital, Spain,

Prospective study

BMI < 18.5 kg/m2 or

BMI = 18.5 -20 kg/m2 and

TST or MAMC < 15th

percentile

Within 48 hours of


400 Not Specified

Undernutrition: 7.8 + 7.2 days, Normonutrition

: 6.2 + 8.0 days

(p = NS)

Undernutrition 30.7% vs.

Normonutrition 20.7%

(p = NS)

Not Specified Not Specified 6 months

SGA = Subjective Global Assessment, LOS = Length of hospital stay, BMI = Body Mass Index, MAC = Mid arm circumference, MAMC = Mid arm muscle circumference, TST = Triceps skinfold thickness, CAMC = Corrected arm muscle area, HR = Hazard ratio, OR = Odds ratio, NS = Non significant

54


Table 1.3: Impact of malnutrition on mortality, length of hospital stay (LOS), readmission and cost, using different nutritional assessment tools and evidence of them being controlled for confounders (continued)

Lead Author


Type of Study

Assessment Tool and


Time of Assessment

and Administrator


for confounders

Duration of outcomes tracking Mortality

/Survival LOS Readmission Cost

BIOCHEMICAL

(Gariballa & Forster,

2007)

Hospitalised patients aged ≥

65 years old, United Kingdom,

Prospective Study

Albumin (cutoff for

malnutrition not specified)

During hospitalization


445

Mean albumin = 38 g/L

(alive) vs. 36 g/L (dead).

Not Specified Not Specified Not Specified

Adjusted for chronic

disease, age, drugs,

functional capacity and acute-phase

response

1 year

(Churchill

et al., 1996)

Patients commencing continuous peritoneal

dialysis in 14 centers in Canada

and United States,

Prospective study

Albumin

(cutoff for malnutrition

not specified)

At the commenceme

nt of peritoneal dialysis,


680

A 1 g/L lower

serum albumin concentration

was associated

with an 6% increase in

the RR of death.

Albumin < 35g/L: 59 days ≥ 35g/L: 20 days

Not Specified Not Specified Not Specified Up to 2 years

(Martineau et al., 2005)

Patients admitted to an

acute stroke unit, Australia,

Prospective study

Albumin: <

35g/L

Within 48 hours of


73 Not Specified

No association between serum

albumin and LOS (r =0.:013,

p = 0:893)

Not specified Not Specified Not Specified During admission

SGA = Subjective Global Assessment, MNA = Mini Nutritional Assessment, LOS = Length of hospital stay, RR = Relative risk, NS = non-significant

55


1.1.5 Potential Confounders for Malnutrition Outcomes Although previous studies have shown a prospective association between

malnutrition and clinical outcomes, the confounding effects of age, gender,

disease and its complexity have seldom been taken into consideration (refer to

Table 1.3).

Previous studies have shown that malnutrition is associated with advancing age

(Rauscher, 1993; Middleton et al., 2001). As people age, they tend to have more

illness, more admissions to hospital and potentially longer lengths of hospital stay.

Hence, in any clinical outcome study, it is important to control the results for age.

Despite this, many studies on malnutrition outcomes did not control for this

(Middleton et al., 2001; Planas et al., 2004; Gupta et al., 2005; Thomas et al.,

2007; Gout et al., 2009). Similarly, outcomes can be affected by gender. For

example, Pirlich (2006) showed that hospitalised females are more likely to be

malnourished than males (Pirlich et al., 2006).

Prospective descriptive studies on the outcomes of malnutrition which control for

the nature and severity of medical condition in adult hospitalised patients are

scarce and none have controlled for the complexity and severity of disease. One

study on adult hospitalised patients controlled for medical conditions but disease

severity was not taken into consideration. In a retrospective study on 709 newly

hospitalised patients in Brazil, Correia & Waitzberg (2003) controlled for

presence of cancer and infection, age over 60 years and those undergoing

clinical treatment. However controlling for just two medical conditions such as

cancer and infection is grossly inadequate as there are different stages of cancer

and severity of infection, as well as many other medical conditions which may

affect patient outcomes. Three other studies have focused on elderly patients,

which controlled for the confounders of age, gender and disease (Miller et al.,

2002; Gariballa & Forster, 2007; Charlton et al., 2012). The study by Miller (2002)

on 1799 older adults (≥75 years old) in the Australian community controlled for

56


age, gender, marital status, smoking, self-rated health, activities of daily living,

comorbidity, cognition and depression (Miller et al., 2002). The authors controlled

for disease using the 10 most prevalent comorbid conditions which are cancer,

arthritis, heart condition, heart attack, hypertension, ulcers, diabetes mellitus,

respiratory disease, hernia and stroke (Miller et al., 2002). Severity of disease

was also not taken into consideration in this study. The other two studies were

also on elderly (≥65 years old) and despite controlling for disease, did not

mention about severity of disease (Gariballa & Forster, 2007; Charlton et al.,

2012).

Controlling an outcome for disease or medical specialty alone is inadequate as

there are different levels of severity and complexities within each disease. For

example, Stage 4 cancer cases differ in complexity and outcome in comparison

to Stage 1 cancer. The diagnoses and complexities of disease based on the

resources used can actually be determined using DRG (Robinson et al., 1987).

The DRG is a system widely used by many countries to cluster patients with a

variety of diagnoses and procedures into diagnostic groups on the basis that

cases within a group will have a similar level of complexity and their treatment is

expected to utilise a similar level of hospital resources and hence incur similar

costs (Thompson, 1988). They are used as a basis for hospital funding allocation

(Thompson, 1988). Each DRG has a specific numerical code as assigned by the

Australian National Diagnosis-Related Groups (Commonwealth Department of

Health and Family Services and 3M Health Information Systems, 1996) or similar

groups. By nature of its widespread adoption across many countries, albeit with

some variation and customization specific to each country, DRG is a convenient

way to collect and compare data of patients with similar disease diagnoses and

complications, to study the effect or association of disease on various end-points

of interest. In order to show that the outcomes of malnutrition are independent of

the underlying disease and its severities, it is possible to adjust the results for

57


DRG. So far no studies have used DRG to control for the confounding effect of

diagnosis on malnutrition outcomes in a multidisciplinary setting.

Besides DRG, there are a variety of other methods which can be used to control

for disease and its severity or complexities such as the Charlson Comorbidity

Index (CCI) (Charlson et al., 1987), Cumulative Illness Rating Scale (CIRS) (Linn

et al., 1968), Index of Coexisting Disease (ICED) (Cleary et al., 1991), Burden of

Disease (BOD) index (Mulrow et al., 1994), Kaplan Index (Kaplan & Feinstein,

1974) and Incalzi Index (Incalzi et al., 1997). All these methods are labour-

intensive, and require clinical assessments or review of patients’ clinical case-

notes to provide a summative weightage of 13-59 items. In addition, the tools

contain limited number of disease categories resulting in some conditions not

being able to be scored, for example the CCI does not list hip fracture, short

bowel syndrome and infection as comorbidities, among others. Kaplan Index was

developed specifically for people with diabetes, and the BOD and Incalzi Index

for the elderly. Despite the limitations of various comorbidity tools, Baldwin et al.

(2006) in a study on four comorbidity methods reported that each is fairly robust

in predicting outcomes, although some comorbidity measures have minor

advantages over others. Therefore, investigators should select a suitable method

based on its availability, staff comfort with the methodology, and outcomes of

interest (Baldwin et al., 2006). Again, no studies have used measures of

comorbidities tools to control for the outcomes of malnutrition.

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Summary of Issues on Clinical Outcomes of Malnutrition

In summary, the adverse outcomes of malnutrition in hospitalised patients are

well-established. Although some studies controlled for effect of disease on

outcomes, there is no published study on the consequences of malnutrition that

has adjusted for disease type and complexity in adult hospitalised patients. It is

important to determine the cost and clinical outcomes arising from malnutrition

and more so to control the outcomes for the confounders that have been

discussed in this section. If healthcare institutions and professionals are

convinced that malnutrition has an impact on clinical outcomes and costs

independent of medical diagnosis, they are more likely to proactively prevent and

manage malnutrition. A prospective study that controls for all the confounders

mentioned above will provide a strong evidence base from which to advocate for

additional resources if it does indeed show an independent association between

malnutrition and outcomes.

59


1.2 NUTRITION SCREENING

Given that malnutrition is commonly unidentified and untreated, (McWhirter &

Pennington, 1994) and increases morbidity and mortality risk, it is important to

identify patients who are at risk and make an accurate diagnosis for these

patients so that early nutrition intervention can be administered. A number of

methods have been developed to both identify risk and/or to diagnose

malnutrition (Guigoz et al., 1996; Lyne & Prowse, 1999). Nutrition screening and

nutrition assessment are typically used for these purposes; however the

delineation between them should be clearly set (Charney, 2008).

Nutrition screening is a process of efficiently identifying characteristics known to

be associated with malnutrition risk (American Dietetic Association., 1994;

American Society for Parenteral and Enteral Nutrition., 2012). Skipper et al.

(2012) defined nutrition screening as a process to identify patients, clients, or

groups who may have a nutrition diagnosis and benefit from nutrition assessment

and intervention by a registered dietitian (Skipper et al., 2012). Its purpose is to

identify those at risk of malnutrition to facilitate nutrition assessment and early

delivery of nutritional intervention (American Dietetic Association., 1994;

American Society for Parenteral and Enteral Nutrition., 2012). A key aspect of

screening is that further information is required to make a diagnosis or treatment

decision (Charney, 2008). However, there is some controversy regarding ‘ideal’

nutrition screening, including choice of screening tool, who should administer

screening, timing of screening and cutoff points to define a ‘positive’ screen

(Charney, 2008). As nutrition screening is to be performed on a large number of

patients, typically all newly admitted patients, the tool has to be simple, quick,

reliable, valid and cost effective (Ferguson et al., 1999a; Charney, 2008).

Acceptable nutrition screening tools are those with a high level of validity,

reliability, efficiency and cost-effectiveness (Lyne & Prowse, 1999; Charney,

2008). In 2006, a group of dietitians from United States, Europe, Australia, and

the Middle East developed a set of guidelines for nutrition screening which

60


stated: (1) it can be used in any practice setting, (2) it should be quick, easy to

use, valid, and reliable for the patient population or setting, (3) the tool and

content should be developed by dietitians and (4) it should be conducted within

an appropriate time frame for the setting (Skipper et al., 2012).

It is recommended that hospitalised patients be screened for nutritional risk

within 24 hours of admission using a nutrition screening tool (Joint Commission

International, 2008). Data collected for nutrition screening should be easily

obtained to minimise incompletion (Charney, 2008). Parameters usually included

in nutrition screening are weight change, adequacy of oral intake and nutrition-

focused physical examinations (Charney, 2008).

There are a number of established nutrition screening tools, including the

Malnutrition Universal Screening Tool (MUST) (Stratton et al., 2004), Nutrition

Risk Index (NRIa) (Veterans Affairs Total Parenteral Nutrition Cooperative Study

Group, 1991) and Malnutrition Screening Tool (MST) (Ferguson et al., 1999a).

Table 1.4 presents the components, strengths and limitations of nutrition

screening tools developed for hospitalised patients. Common limitations of

current tools are high levels of missing data (for BMI, weight and biochemical

data), ambiguity (for appetite, nutritional intake, pressure ulcers and disease),

length of questionnaire, time-consuming to administer, no cutoff for referral to

dietitians and no option for patients who are unsure of their weight loss.

61


Table 1.4: Components, strengths and limitations of nutrition screening tools for hospitalised patients (in alphabetical order) Tools Components Strengths Limitations Derby Nutritional Score (Goudge et al., 1998)

a) Body weight for height b) Mobility/capability c) Gastrointestinal (GI) Symptoms d) Skin type e) Appetite and dietary f) Intake g) Psychological state h) Age

Non-invasive

Indicates score for action plan

Missing data for patients unfit to be weighed and measured for height No mention of length of period for GI symptoms or poor appetite Questionnaire of 7 items may be deemed too lengthy for busy staff

Malnutrition Screening Tool (MST) (Ferguson et al., 1999a)

a) Lost weight recently without trying b) Quantity of weight loss c) Eating poorly because of decreased

appetite

Easy to use Option of ‘unsure’ for patient who are not sure of weight loss Quick Non-invasive Indicates cutoff score for referral process

Malnutrition cutoffs may be confounded by ethnicity/ population

Malnutrition Universal Screening Tool (MUST) (Stratton et al., 2004)

a) BMI b) % Unplanned weight loss in 3-6

months c) No or likely to be no nutritional intake

for >5 days

Easy to use Non-invasive Indicates cutoff score for referral process Directs clinicians in nutrition care plan

Missing data for patients unfit to be weighed and measured for height Many nurses do not carry calculator to calculate BMI (reference to BMI charts an extra step) Results inaccurate for subjects with fluid retention or dehydration High incomplete screening No option for patients who are unsure of weight loss Malnutrition cutoffs may be confounded by ethnicity/ population

Mini Nutritional Assessment-Short Form (MNA-SF) (Rubenstein et al., 1999)

a) Loss of appetite b) Weight loss in the past 3 months c) Mobility d) Psychological stress or acute

disease in the past 3 months e) Neuropsychological problems f) Body Mass Index

Specifically designed for use in the elderly community population

Limitations of BMI as mentioned above Limited to the use in the elderly and community Need to use a different tool for younger patients

Nutrition Risk Index (NRIa)

(Veterans Affairs Total Parenteral Nutrition Cooperative Study Group, 1991)

a) Serum albumin b) Current weight c) Usual weight

Objective parameter Indicates cutoff score for referral process

Results are inaccurate as albumin is easily affected by inflammation, fluid retention or dehydration Missing data for patients unfit to be weigh or measured for height Does not direct clinicians in nutrition care plan

Validation of nutrition screening tools is shown in Table 1.6

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Table 1.4: Components, strengths and limitations of nutrition screening tools for hospitalised patients (continued) Tools Components Strengths Limitations Nutritional Risk Index (NRIb) (Wolinsky et al., 1985)

a) Dentures b) Prescriptive medications c) Non-prescriptive medications d) Abdominal operation e) Bowel problems f) Food intolerance g) Mastication problems h) Conditions affecting food intake i) Smoking j) Special diet k) Anemia l) Stomach or abdominal pain m) Illness leading to loss of appetite n) Swallowing problems o) Vomiting p) Weight changes

One of the pioneer nutrition screening tools Comprehensive Non-invasive Indicates cutoff score for nutritional risk

Lengthy 16-items question Time-consuming to complete Limited to the use in elderly

Nursing Nutritional Assessment Tool (Scanlan et al., 1994)

a) BMI b) Appetite c) Swallowing, d) Diet e) Weight change f) Medical/physical condition g) Postoperative status

Non-invasive Indicates cutoff score for action plan and referral to dietitian

Lengthy 7-items question Time-consuming to complete Limitations for BMI as mentioned above

Nutrition Risk Score (NRS) (Reilly et al., 1995)

a) Weight loss in the last 3 months b) BMI c) Appetite d) Ability to eat or retain food e) Stress factor

Non-invasive One single tool for use in both paediatric and adult patients

No cutoff score within the tool for referral process Limitations for BMI as mentioned above Results may not truly indicate malnutrition as it is marred by severity of illness

Nutrition Risk Classification (Kovacevich et al., 1997)

a) Ideal body weight b) Weight loss history c) Alterations in dietary intake d) Gastrointestinal function

Non-invasive Missing data for patients unfit to be measured for height to calculate ideal body weight Many nurses do not carry calculator to calculate ideal body weight (reference to charts an extra step)

Nutrition Risk Check (Rawlinson, 1998)

a) Weight loss b) Appetite c) Ability to eat d) Gut function e) Medical condition f) Pressure ulcer assessment

Non-invasive

Indicates staggered cutoff score for action plan and referral to dietitian

Lengthy questionnaire and action plans Time-consuming to complete Limited details provided on pressure ulcer assessment Nurses may not know how to score other medical conditions not listed are present

Validation of nutrition screening tools shown in Table 1.6

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Table 1.4: Components, strengths and limitations of nutrition screening tools for hospitalised patients (continued) Tools Components Strengths Limitations Nutritional Screening Tool (Scott & Hamilton, 1998)

a) Body weight for height b) Skin type c) Appetite and dietary intake d) Ability to eat e) Symptoms f) Psychological state g) Age

Non-invasive Limitations of BMI as mentioned above Takes time to complete Skin type assessment is subjective and vague

Nutrition Assessment Score (Oakley & Hill, 2000)

a) Appetite b) Weight loss, c) General condition d) Clinical state e) Increased requirements because of

disease states

Non-invasive

Indicates score for action plan

Nurses may not know how to score other medical conditions not listed are present i.e. renal failure, hip fracture, trauma.

Nutrition Screening Tool (Burden et al., 2001)

a) Age b) Mental condition c) Weight status d) Dietary intake e) Ability to eat f) Medical condition g) Gut function

Non-invasive Indicates score for action plan

Patient with co-morbidities (mental status, medical condition and gut-function) may be over-rated. Hence, results may not truly indicate malnutrition risk Patient on tube feeding but receiving adequate nutrition are scored poorly

Nutritional Risk Screening 2002 (NRS 2002) (Kondrup et al., 2003b)

a) BMI b) Weight loss in the last 3 months c) Reduced dietary intake in the last

week d) Severity of illness e) Age

Non-invasive Indicates cutoff score for referral process Directs clinicians in nutrition care plan

Some staff may find it complicated as it has 2 sections Limitations for BMI as mentioned above No option for patients who are unsure of weight loss Results may not truly indicate malnutrition as it is marred by severity of illness

Nutrition Screening Tool (Weekes et al., 2004)

a) Unintentional weight loss in the last 6 months

b) Unintentionally eating less in the last 6 months

c) Nil by mouth or unable to eat > 5 days With option for the nurse to complete BMI and mid arm circumference (MAC)

Non-invasive

Indicates cutoff score for action plan

No option for patients who are unsure of weight loss Confusing and complicated if the nurses also need to complete BMI and MAC


64


Table 1.4: Components, strengths and limitations of nutrition screening tools for hospitalised patients (continued) Tools Components Strengths Limitations Screening Nutritional Profile (Hunt et al., 1985a)

Twelve-item questionnaire to be completed by admission staff / patient followed by anthropometric by nurses and albumin by dietitian: a) Weight loss b) Appetite c) Vomiting / Diarrhoea d) Medical condition e) Surgery f) Fever g) Diet restrictions h) Medications i) Weight j) Height k) Head circumference (children) l) Albumin

Can be used for both adults and children

The 3 step procedure requires the admission staff, nurses and dietitians to complete the form. Invasive and costly – requires blood test Albumin is easily affected by inflammation, fluid retention or dehydration High rate of missing data for weight, height and albumin

Screening Sheet (Thorsdottir et al., 1999)

a) BMI b) Weight loss c) Age d) Symptoms e) Length of hospital stay, f) Surgery type

Non-invasive Takes time to complete Tedious due to need for information on surgery type and length of hospital stay in the past 2 months Limitations of BMI as mentioned above Geared toward surgical patients Cutoff score for action not stated

Short Nutritional Assessment Questionnaire (SNAQ) (Kruizenga et al., 2005a)

a) Unintentional weight loss in 6 months

b) Decreased appetite in 1 month c) Use of supplemental drinks or

tube feeding over the last month

Easy to use

Quick

Non-invasive

Indicates cutoff score for referral process

Confusion on whether the tool is used for identifying risk or diagnosing malnutrition No option for patients who are unsure of weight loss Patient on supplemental drink or tube feeding but receiving adequate nutrition are scored poorly

Simple Screening Tool (Laporte et al., 2001a)

a) BMI b) Weight loss (%)

OR a) BMI b) Albumin

Simple 2 question per screening

Confusing due to the ‘two in one’ screening tool Albumin is easily affected by inflammation, fluid retention or dehydration Limitations of BMI as mentioned above


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1.2.1 Practical Considerations in Nutrition Screening

Nutrition screening must be practical to be of use in clinical practice. Practical

considerations before implementing a screening tool are discussed in the

following sections.

User-friendliness of nutrition screening tool

The ease of use of a nutrition screening tool is important. The tool must be user-

friendly in order to encourage compliance and completion of screening. The

lengthy questionnaires of Nutritional Risk Index (NRIb) (Wolinsky et al., 1985) and

Screening Nutritional Profile (Hunt et al., 1985a) decrease the applicability of the

tool, especially in the busy healthcare setting. Nutritional Risk Index contains 16

questions which incorporates nutritional intake, medications, smoking habits,

illness or medical procedures affecting food intake, changes in eating habits and

weight changes (Wolinsky et al., 1985; Wolinsky et al., 1986). Screening

Nutritional Profile consists of a twelve-item questionnaire to be completed by

admission staff, followed by anthropometric measurement by nurses and review

of albumin levels by dietitians (Hunt et al., 1985a).

Nutrition screening ideally should use easily obtainable data to increase

completion rate. The Nutrition Risk Index (NRIa) assesses nutritional risk using

serum albumin concentration and percentage weight loss from usual weight

(Veterans Affairs Total Parenteral Nutrition Cooperative Study Group, 1991). The

use of albumin level is potentially problematic, as not all inpatients have their

albumin levels routinely checked. In a Singapore study by Lim et al. (2009), only

46% of patients had their serum albumin tested within the first two days of

admission (Lim et al., 2009). If this is not included as part of routine medical care,

obtaining a blood sample for the purpose of nutrition screening could be

considered invasive and expensive (Lim et al., 2009). In addition, serum albumin

is confounded by inflammation (de Mutsert et al., 2009) and disease severity in

66


hospitalised patients and may be inappropriate as a measure of nutritional risk or

status per se (Klein, 1990; Haupt et al., 1999; Shenkin, 2006). In a prospective

study of 225 pre-surgery patients, abnormal concentrations of acute phase

proteins (indicating an acute phase response) were detected in 19% of patients.

The mean albumin concentration in these patients (35g/L) was lower than that of

patients who did not mount an acute phase response preoperatively (40g/L)

(Haupt et al., 1999). This study shows that a metabolic response to disease,

referred to as an acute phase response, can lead to low albumin concentrations

and hence confound the use of albumin to define nutritional risk or status (Haupt

et al., 1999). Therefore it can also lead to over-diagnosis of malnutrition

(Rosenthal et al., 1998).

Another parameter that is often used in nutrition screening tools but is difficult to

obtain is the BMI. There are many nutrition screening tools that require patients’

weight and height or knee height to be measured to calculate BMI. Examples of

screening tools that contain BMI as one of their components include the NRS

(Reilly et al., 1995), MUST (Elia, 2003) and NRS 2002 (Kondrup et al., 2003a).

Weight and height measurements required in BMI pose challenges in patients

who are bed bound or old and frail. In an audit done on 526 hospital episodes,

only 41% had information on both weight and height (Campbell et al., 2002). An

audit in three English hospitals on the use of the MUST nutrition screening tool,

which includes BMI as one of three screening criteria, reported that one-third of

patients remained unscreened, even after specific training of clinical staff to

increase screening completions (Wong & Gandy, 2008; Porter et al., 2009). Even

in the research arena, where missing data has to be minimised, many

researchers faced difficulties in obtaining complete BMI data for their studies

(Kelly et al., 2000; Waitzberg et al., 2001; Correia & Campos, 2003; Wyszynski et

al., 2003). In one of these studies, BMI was not available in 35% of the subjects

even when the researchers actively tried to measure the weight and height

themselves (Kelly et al., 2000). In clinical practice, unavailable weight, height and

BMI records can be as high as 74-85% (Waitzberg et al., 2001; Correia &

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Campos, 2003; Wyszynski et al., 2003; Neelemaat et al., 2011b). The

measurement challenges discussed above limit the utility of nutrition screening

tools which combine BMI with other parameters. This further strengthens the

argument that BMI is not a practical parameter for nutrition screening.

Realising the challenges of obtaining patients’ BMI, a few authors have come up

with alternative anthropometric measures or subjective assessment (Stratton et

al., 2006; Kaiser et al., 2009; Kaiser et al., 2011). For example, if weight could

not be measured in MUST, the author recommended the use of ‘recalled weight’.

If neither weight nor height could be obtained, subjective assessments of

physical appearance (very thin, thin etc.), were employed (Stratton et al., 2006).

Given the difficulties in obtaining weight and height data for many patients, the

use of surrogate anthropometric markers is an advantage for MUST. However,

the reliability of these methods to estimate BMI or physical appearance has not

been validated and their accuracy remains questionable. An alternative to

obtaining the weight and height of patients not able to sit or stand is to use the

bed weighing machine or the knee height measurement (Stratton et al., 2006;

Cereda et al., 2007). However each bed weighing machine costs about S$10,000

and not many hospitals can afford to purchase one for each of their wards. In

addition, these patients need to be transferred from their hospital bed to the

weighing bed and back, creating extra demand for resources and manpower.

Low nurse to patient ratios in Asian hospitals (specifically 1 nurse to 7 patients in

NUH in the year 2002) are a further barrier to such measurements. Therefore,

nutrition screening tools which require these measurements may not be suitable

in hospitals with low nurse to patient ratios.

Cutoff for risk of malnutrition Body Mass Index (BMI) has often been used as a screening parameter for a

range of medical conditions (Foucan et al., 2002; Iseki et al., 2004; Pua & Ong,

2004; Norberg et al., 2006; Lloyd-Jones et al., 2007; Onalan et al., 2009; Sanada

68


et al., 2012). Although a high BMI has much supporting evidence for use as a

marker of cardiovascular disease risk such as heart disease, hypertension and

diabetes (Sung & Ryu, 2004; Hoad et al., 2010; Sanada et al., 2012), there is no

established cutoff point of the lower end of BMI to signify risk of malnutrition.

Body Mass Index and its associated cutoffs may be confounded by ethnicity,

changes in body composition, fluid retention commonly associated with illness

and reduction in height with ageing-related kyphosis (Nightingale et al., 1996;

Deurenberg-Yap et al., 2000; Kondrup et al., 2003b; Shirley et al., 2008). Body

Mass Index does not distinguish between major components of body weight (fat,

lean body mass and fluid). It is common for clinicians to consider underweight

patients as malnourished and patients with normal or high BMI as being well

nourished. However as a stand-alone marker, this can be misleading and may

result in over or under-diagnosis of malnutrition. Patients who have normal or

elevated BMI may have lost substantial body weight, placing them at nutritional

risk even if their BMI remains in the normal range. People of Asian ethnicity may

have a small frame or be classified as underweight based on BMI, yet are

healthy.

Different studies have used different BMI cutoffs for malnutrition (Kelly et al.,

2000; Thomas et al., 2002; Kyle et al., 2003). While Kelly et al (2000) rationalised

using BMI 18.5 kg/m2 as a cutoff for malnutrition based on World Health

Organisation recommendations, the remaining authors did not give a reason for

adopting a specific BMI cutoff for malnutrition. Deurenberg et al. (2001) found

that Asians have a different body composition from Caucasians and hence

require different cutoffs for BMI in overnutrition (Deurenberg-Yap et al., 2000;

Deurenberg & Deurenberg-Yap, 2001). Therefore it is likely that the cutoffs for

malnutrition risk will similarly differ for different populations even when the same

nutrition screening tool is used.

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Confusion between screening and assessment There is some lack of clarity in the literature regarding screening and

assessment. The naming convention of a few screening tools poses some

confusion to healthcare staff. For example, Nutrition Assessment Score (Oakley

& Hill, 2000), Nursing Nutritional Assessment Tool (Scanlan et al., 1994) and


which were developed as screening tools but were named as assessment tools.

The SNAQ uses a score of ≥ 2 to indicate moderate malnutrition and ≥ 3 as

severe malnutrition, adding to the confusion between risk and diagnosis of

malnutrition (Kruizenga et al., 2005a). Some investigators have used screening

tools to determine the nutritional status of patients (Bruun et al., 1999; Vanis &

Mesihovic, 2008; Gur et al., 2009), whereas in best practice, a nutrition

assessment tool should be used. Bruun et. al (1999) used BMI and weight loss to

assess nutritional status of surgical gastrointestinal and orthopaedic patients,

while Gur et. al. (2009) used NRS-2002 to determine the prevalence of

malnutrition in newly admitted surgery patients. Another example is the BMI,

which is used in some studies as part of a screening tool (Kondrup et al., 2003b;

Stratton et al., 2004) and used in others as part of an assessment tool to

determine nutritional status (McWhirter & Pennington, 1994; Landbo et al., 1999;

Kelly et al., 2000; Thomas et al., 2002; Kyle et al., 2003; Pirlich et al., 2006).

Body Mass Index has been incorporated into many screening tools, supporting

the fact again that by using BMI alone one cannot determine the nutritional status

of an individual (Kondrup et al., 2003a).

A single screening tool for an institution

In very large acute care hospitals, it is not practical to have different nutrition

screening tools for different disease and age groups. Notwithstanding, it is widely

agreed to be necessary to take a different approach for adult versus paediatric

patients. The aim of a single adult screening tool is to minimise confusion among

70


staff, standardise practice and conserve resources in training staff when they are

deployed from one ward to another. However, a number of age or disease

specific tools have been developed. For example, MNA-SF has been developed

for use with the elderly (Rubenstein et al., 1999) and Malnutrition-Inflammation

Score (MIS) has been developed for patients on haemodialysis (Kalantar-Zadeh

et al., 2001). The MNA-SF (Rubenstein et al., 1999) was developed from the

original 18-item MNA (Guigoz et al., 1994; Guigoz et al., 1996) by Nestlé in

France as a screening tool specifically for the elderly ( ≥ 65 years old) and its use

has been limited mainly to this group of patients (Anthony, 2008). Both the MNA-

SF and MIS have been validated and are frequently used in nursing homes and

long term care facilities and dialysis centres respectively; and in these settings

have served their purpose well (Rubenstein et al., 1999; Kalantar-Zadeh et al.,

2001; Kalantar-Zadeh et al., 2003; Guigoz, 2006). Such targeted tools may be

more sensitive to the needs of their specific populations. However in the hospital

setting where there are patients with a wide age range of age and disease

conditions, it is not practical to carry out MNA-SF on the elderly, MIS on dialysis

patients and use a separate tool for the rest of the patients. At most, there should

only be separate nutrition screening tools for adult and paediatric patients, where

a small change in a nutritional parameter may have a more significant implication

for a child compared to an adult. For example a weight loss of one kilogram in a

two-month-old infant is highly significant whereas in an adult it may not be.

Similarly, failure to gain weight in a certain period of time is of significant concern

in a growing child. Screening tools developed for specific medical conditions or

age groups are summarised in Table 1.5.

For the reasons mentioned above, nutrition screening tools which are disease- or

age-specific will be excluded from literature review henceforth, unless prior

validation study in general adult hospitalised patients across different age and

disease groups has been carried out, and the tool found to be suitable for use in

hospital adult patients as a whole.

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Table 1.5: Nutrition screening tools developed for targeted groups of people Targeted groups Nutrition Screening Tool

Adult with learning difficulties

• Nutrition Screening Tool (Bryan et al., 1998)

Critically ill • Prognostic inflammatory and nutritional index (Ingenbleek & Carpentier, 1985)

• Nutrition Risk in the Critically ill Score (NUTRIC Score) (Heyland et al., 2011)

Community • Nutrition Screening Equation (Elmore et al., 1994)

• Nutrition Risk Score (Reilly et al., 1995) • Community Focused Nutritional Screening Tool

(Gilford & Khun Khun, 1996) • Nutrition Assessment Tool (Hickson & Hill,

1997) • Screening in Practice (Ward 1998) • Community Nutrition Risk Assessment

(Bartholomew et al., 2003)

Children with special healthcare needs

• Nutritional Screening Test (Henderson et al., 1992)

• PEACH Survey (Campbell & Kelsey, 1994) • Nutrition and Feeding Risk Identification Tool

(Baroni & Sondel, 1995) • Pediatric Nutritional Risk Score (Sermet-

Gaudelus et al., 2000) • STRONG(kids) (Hulst et al., 2010)

Dialysis • Dialysis Malnutrition Score (DMS) (Kalantar-

Zadeh et al., 1999) • Malnutrition-Inflammation Score (MIS)

(Kalantar-Zadeh et al., 2001) • Screening Tool (Gower, 2002) • Objective Score of Nutrition on Dialysis

(Beberashvili et al., 2010)

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Table 1.5: Nutrition screening tools developed for targeted groups of people (continued) Targeted groups Nutrition Screening Tool

Elderly • Nutrition Screening Tool (Noel & Wojnaroski, 1987)

• Nutrition Risk Index (Veterans Affairs Total Parenteral Nutrition Cooperative Study Group, 1991)

• DETERMINE (White et al., 1992) • Nutrition Score (Charalambous, 1993) • Nutritional Risk Assessment Scale (Nikolaus et

al., 1995) • Nursing Nutritional Screening Tool (Cotton et

al., 1996) • Mini Nutritional Assessment – Short Form

(MNA-SF) (Rubenstein et al., 1999) • Nursing Nutrition Screening Assessment

(Pattison et al., 1999) • Simple Screening Tool (Laporte et al., 2001b) • Nutritional Risk Screening 2002 (Kondrup et al.,

2003b) • Rapid Screen (Visvanathan et al., 2004) • New Screening Tool (Charlton et al., 2005) • Geriatric Nutritional Risk Index (Bouillanne et

al., 2005) Oncology • Nutritional Screen Form (Lundvick & Phillips,

1983) • General Nutritional Status Score (GNS) (Guo et

al., 1994) • Oncology Screening Tools (Latkany et al.,

1995) • Patient-generated Subjective Global Screening

(VSG-GP) (Gomez Candela et al., 2010) Preoperative surgery

• Prognostic Nutritional Index (Buzby et al., 1980) • Maastricht Index (Kuzu et al., 2006)

Psychiatric • St Andrew's Nutrition Screening Instrument (SANSI) (Rowell et al., 2012)

Surgical • Undernutrition Risk Score (Doyle et al., 2000) Trauma • Nutrition Checklist (Cooper, 1998)

73


1.2.2 Validity of Nutrition Screening Tools

For a nutrition screening tool to be accurate and useful, it has to be valid and

reliable (Charney, 2008). Any screening procedure must have an acceptable

level of sensitivity and specificity, relative to some definitive diagnostic procedure

or “gold standard” (Rush, 1993). Sensitivity (the ability to identify true cases) is

important where the consequences of an undetected case may be significant.

Specificity (the ability to classify correctly those without the condition) is important

to avoid labeling someone with an incorrect presumptive diagnosis, which may

result in anxiety for the patient, unnecessary procedures and costs (Rush, 1993).

Jones (2002) critically appraised 44 published reports on nutrition screening and

assessment tools and found that only two-thirds assessed validity. Of the 44

studies appraised, 8 were studies using tools developed for hospitalised adult

patients (all medical conditions), of which only 5 were validation studies.

However, the review did not compare the sensitivity and specificity of the tools

(Jones, 2002). The sensitivity and specificity of tools allow comparison between

the tools to determine which tool to adopt. A nutrition screening tool that has high

sensitivity but low specificity may cause too many patients to be referred to the

dietitians unnecessarily and waste resources. For example the South

Manchester University Hospitals Trust’s Nutrition Screening Tool (NST) (Burden

et al., 2001) was 78% sensitive and 52% specific, which meant that about half of

well-nourished patients were identified as at risk of malnutrition. This is likely

caused by over-scoring of patients with co-morbidities, as mental status, medical

condition and gut-function are scored separately. Patients on tube feeding

receiving adequate nutrition were also scored poorly. Hence, the tool might have

identified too many patients who were not truly at malnutrition risk, resulting in

the low specificity of the tool. On the other hand, a tool that has low sensitivity but

high specificity is more worrying as many patients who are malnourished will not

receive the necessary intervention. A validation study on 995 inpatients in a

74


hospital in Switzerland showed that although the specificity of NRI was good

(89%), its sensitivity was only 43% when compared against SGA (Kyle et al.,

2006). This is a concern as many malnourished patients will be missed out if NRI

tool is used.

Green and Watson reviewed 35 papers on nutrition screening and assessment

tools from the year 1982 to 2002, of which 13 were studies on nutrition screening

tools developed for use on adult hospitalised patients, 7 were on nutrition

assessment tools (mostly SGA or the modified version of SGA) and 15 were on

screening tools developed for children, community care or specific medical

conditions (Green & Watson, 2005). The authors found that many of the

published tools did not go through rigorous testing (Green & Watson, 2005).

Similar to the study by Jones (2002), the review did not provide information on

the reliability, sensitivity and specificity of the tools or whether the studies were

conducted in a blinded manner (Green & Watson, 2005).

Table 1.6 presents the validity and reliability of nutrition screening tools in

hospitalised adult patients. For nutrition screening tests, van Venroij (2007)

recommended sensitivity and specificity of at least 65% as acceptable (van

Venrooij et al., 2007). However this would depend on the relative importance of

detecting at risk patients and the resources (dietitian) needed to attend to

patients who were identified at risk. The higher the sensitivity and specificity of a

tool, the better. The validity of a nutrition screening tool can be determined by

validating it against a gold standard (Jones, 2004b). There is no consensus on

the gold standard of a nutrition assessment tool to define malnutrition. For

example, MUST was validated against seven nutritional screening and

assessment tools in the United Kingdom (Stratton et al., 2004), NRS was

validated against NRIb (Reilly et al., 1995) and MST validated against SGA in

Australia (Ferguson et al., 1999a; Ferguson et al., 1999b; Isenring et al., 2009).

The agreement between MUST and the various reference standards varies

according to reference standards; from poor agreement (r=0.255) when validated

75


against Undernutrition Risk Score to excellent agreement (r=0.775) when

validated against NRS (Stratton et al., 2004). Subsequent validation studies on

MUST by different investigators showed low sensitivities ranging from 54% to

61% (Bauer & Capra, 2003; Kyle et al., 2006; Lawson et al., 2012). All validation

studies on MST have used SGA as the gold standard with sensitivity ranging

from 41% to 100% (Ferguson et al., 1999a; Ferguson et al., 1999b; Lawson et

al., 2012).

Although many nutrition screening tools have been developed in various

countries, none have yet been developed and published in Asia. Many screening

tools such as the Nursing Nutritional Assessment Tool (Scanlan et al., 1994),

Nutrition Risk Check (Rawlinson, 1998) and Nutritional Screening Tool (Scott &

Hamilton, 1998), have not been validated even years after being developed. Yet

others such as the Nutrition Risk Score (Reilly et al., 1995), Derby Nutritional

Score (Goudge et al., 1998) and Nutrition Screening Tool (Weekes et al., 2004),

did not perform analytical accuracy testing on their tools, hence the sensitivity

and specificity of the tools are not known. These and other validation studies

presented in Table 1.6 showed that some of the screening tools were validated in

various clinical and healthcare settings across different countries, using different

reference standards, with different results. The most commonly used reference

standard for validation of nutrition screening tools was SGA, which will be

discussed further in section 1.2.4.

Nutrition screening administered by nurses in validation studies A survey carried out in the USA showed that only 10% of nutrition screening was

administered by nutrition services staff, in comparison to 84% by nursing staff

and 4% by a computerized system (Chima et al., 2008). Nurses have the first

and regular contact with every patient upon admission, hence they are the most

suited to carry out nutrition screening on patients upon admission (Johnstone et

al., 2006a; b). Having dietetic staff to conduct nutrition screening is costly and not

76


feasible in many institutions. Lyne and Prowse (1999) shared the need for a

simple, effective and valid nutrition screening tool for nurses to prevent non-

compliance (Lyne & Prowse, 1999).

Although in practice nutrition screening is commonly undertaken by nursing staff,

few studies have used nurses to validate nutrition screening tools. Most studies

have used researchers, dietitians or dietetic staff to implement nutrition screening

(Ferguson et al., 1999a; Kyle et al., 2006; Kim et al., 2011; Velasco et al., 2011).

Kim et al (2011) used dietitians to test the validity of the Malnutrition Screening

Tool for Cancer Patients (MSTC) against PG-SGA. The sensitivity and specificity

of MSTC was 94% and 84% with high agreement (k= 0.7) (Kim et al., 2011). The

Malnutrition Screening Tool (MST) was developed to screen acute care patients

and validated against SGA by one dietitian, with a sensitivity and specificity of

93% (Ferguson et al., 1999a). The same tool was shown to be an effective

screening tool in comparison to PG-SGA when administered by researchers, with

100% sensitivity and 92% specificity (Isenring et al., 2006). Previous validation

studies which used nursing staff to administer screening and a dietitian to

complete nutrition assessment were with the British Nutrition Screening Tool

(NST) (Mirmiran et al., 2011), MST (Nursal et al., 2005a), Screening Sheet

(Thorsdottir et al., 1999) and MUST (Lawson et al., 2012), with sensitivity and

specificity ranging from 49 -85% and 63-85%, respectively.

Ideally, the assessor for the tool and the reference standard should be

independent, and blinded to each other’s results to prevent bias in validation

studies. Table 1.6 shows that most validation studies on nutrition screening tools

did not utilise blinding of the assessors. In the original validation study on MUST,

none of the assessors were blinded and the study showed good agreement with

SGA (k = 0.783) (Stratton et al., 2004). In two validation studies on MUST and

MST, the assessors were blinded to each other’s results but the results showed

poor sensitivities (59%, 54% and 49%) when compared to SGA (Bauer & Capra,

2003; Lawson et al., 2012). Two other studies which conducted blinding of the

77


assessors found the specificity of the Nutrition Screening Tool to be poor (62%)

(Mirmiran et al., 2011) or did not report on the results (Weekes et al., 2004).

1.2.3 Reliability of Nutrition Screening Tools

Reliability means results have to be consistent and reproducible. Inter-rater

reliability is the variation in results or measurements when assessed by different

persons using the same tool at the same time (Jones, 2004a). Intra-rater

reliability is the variation when the measurement is repeated by the same person

using the same tool at different times. However reliability does not imply validity.

A reliable tool may be able to produce the same results consistently when used

by a different assessor, but it may not necessarily give correct or accurate

results. Most studies have used kappa coefficient as a statistical measure to

determine inter-rater agreement. Fleiss (2003) defined a kappa of above 0.75 as

excellent, 0.40 to 0.75 as fair to good and below 0.40 as poor (Fleiss et al.,

2003). Among the nutrition screening tools, inter-rater reliability studies have

been performed on many of them, including MST (Ferguson et al., 1999a), NRS

(Reilly et al., 1995) and NST (Burden et al., 2001).

Similar to validity studies, many inter-rater reliability tests have been performed

on nutrition screening tools that compared the results of dietitian with dietitian, or

dietitian with nursing staff (Reilly et al., 1995; Ferguson et al., 1999a; Burden et

al., 2001). These studies generally show good agreement. Inter-rater agreement

between dietetic staff using MST was found to be excellent at 96% (r = 0.93-0.96,

Kappa = 0.84-0.88) (Ferguson et al., 1999a), and similarly research and nursing

staff implementing MST also shows high inter-rater reliability (k = 0.82, p<0.001)

(Isenring et al., 2006). Nutrition Risk Screening (NRS) shows good inter-rater

reliability when administered by dietitians (r=0.91, p<0.001) or by dietitians and

nurses (r=0.80, p<0.001) (Reilly et al., 1995). In contrast, McCall and Cotton

found poor agreement between dietitian and nurse administering the Nursing

Nutritional Assessment (NNA) (McCall & Cotton, 2001).

78

http://en.wikipedia.org/wiki/Validity_(psychometric)�


A nutrition screening tool should also be tested for inter-rater reliability among the

end-users, which are often the nurses. Only two studies examining inter-rater

reliability between nurses have been identified (McCall & Cotton, 2001; Mirmiran

et al., 2011). In the study by Mirmiran et al. (2011), two nursing staff administered

the British Nutrition Screening Tool (NST) on 446 newly admitted patients, with a

good level of agreement (Kappa = 0.71) (Mirmiran et al., 2011). In contrast,

McCall and Cotton (2001) found consistent disagreement between nursing staff.

The reliability study on NNA was carried out by two nurses on 185 patients

admitted to an ‘acute elderly’ ward and the coefficient for the tool as a whole was

0.53. The authors attributed the poor inter-rater reliability between dietitian and

nurse, and nurse and nurse, to subjective interpretation of questions within the

tool (McCall & Cotton, 2001).

Summary of Issues related to Nutrition Screening Tools

There is no consensus on the best method for nutrition screening. The selection,

reporting and interpretation, including cutoffs, of nutrition screening may differ

between different racial groups, healthcare systems and cultural contexts. In

addition, a nutrition screening tool should be user friendly and use easily

obtainable data, not time-consuming, non-invasive, simple (not too lengthy) and

inexpensive. The limitations of current tools are their complexities, high rate of

missing data, age specificity, specialty specificity, cultural barriers and being not

user-friendly. These warrant the development of a new screening tool for acute

hospitals in Singapore, suitable for use across different diagnostic and adult age

groups (≥ 21 years old). Despite the variation in culture and needs, there has not

been any nutrition screening tool developed and validated for acute care

hospitals in Asia. In the last decade, most validation studies on nutrition

screening tools in Australia, Europe and the United States have used SGA as the

reference standard. However these studies did not perform blinding of the

79


assessors nor use the intended or most likely assessor (nurses) to conduct the

screening in their studies.

80


Table 1.6: Reliability and validity of nutrition screening tools in hospitalised adult patients* and method of validation, including blinding of assessor (excluding tools developed for older adults, community and specific medical conditions)

SGA = Subjective Global Assessment, MST = Malnutrition Screening Tool, k = kappa score

*Further validation studies conducted on patients with specific medical condition are presented, only if the tool has previously been validated in general hospitalised adult patients

Tool (Lead author)

Participants, Country

Reliability Relative validity

Number of

subjects

Number

of raters

Inter-rater reliability Number

of

subjects

Reference

standard

Assessor for tool and

reference standard/

Blinding

Sensitivity Specificity

Malnutrition Screening Tool (MST)

MST (Ferguson et al., 1999a)

Hospital inpatients

(Australia)

32 2/3 Agreement between

2 dietitians = 96%

(k = 0.88),

Agreement between

a dietitian and

nutrition assistant =

93% (Kappa = 0.84)

408 SGA 1 dietitian, not blinded 93% 93%

MST (Ferguson et al., 1999b)

Oncology patients

undergoing

radiotherapy*

(Australia)

Not evaluated 106 SGA 2 dietitians, blinding not

specified

100% 81%

MST (Nursal et al., 2005a)

Hospital inpatients

(Turkey)

2181 2 Agreement between

1 dietitian and 1

nurse (k = 0.72)

2211 SGA 1 dietitian and 1 nurse,

blinding not specified

74% 76%

MST (Lawson et al., 2012)

Hospitalised renal

patients* (United

Kingdom)

23 ≥ 2 Agreement between

2 nurses (k = 0.33)

145 SGA Dietitians conducted the

SGA.

Nurses or nursing students

conducted the MST.

Investigators mostly

blinded.

49% 86%

81


Table 1.6: Reliability and validity of nutrition screening tools in hospitalised adult patients* and method of validation, including blinding of assessor (continued)

Tool (Lead author)



Number

of

subjects

Number

of raters

Inter-rater reliability Number

of

subjects

Reference

standard

Assessor for tool and reference

standard/ Blinding


Malnutrition Universal Screening Tool (MUST)

MUST (Stratton et al., 2004)

Hospitalised

patients

(United Kingdom)

Not evaluated

75

75

86 & 85

50

52

NRS (Medical)

MST (Medical)

MNA (Elderly)

MNA (Surgical)

SGA (Medical)

URS (Surgical)

1 assessor conducted test tool

and reference standards except

for MNA which had 2 assessors.

All not blinded. Assessors were

trained by dietetic research fellow

and physician.

k = 0.775,

& 0.813

k= 0.707

k = 0.551

k= 0.605

k = 0.783

k= 0.255

& 0.431

Not

specified

MUST (Kyle et al., 2006)

Medical and

surgical inpatients

(Switzerland)

Not evaluated 995 SGA 2 trained co-workers performed

both MUST and SGA; not blinded

61% 76%

MUST (Bauer & Capra, 2003)

Hospitalised

oncology patients*

(Australia)

Not evaluated 65 SGA 2 experienced dietitian performed

SGA and MUST independently;

blinded

59% 75%

MUST (Lawson et al., 2012)

Hospitalised renal

patients* (United

Kingdom)

29 ≥ 2 Agreement between

2 nurses:

Kappa = 0.58

147 SGA Dietitians conducted the SGA.

Nurses or nursing students

conducted the MUST.

Investigators mostly blinded.

54%

78%

SGA = Subjective Global Assessment, MUST = Malnutrition Universal Screening Tool, NRS = Nutrition Risk Score, MST = Malnutrition Screening Tool, MNA = Mini Nutritional

Assessment, URS = Undernutrition Risk Score, k = Kappa score

*Further validation studies conducted on patients with specific medical condition are presented, only if the tool has previously been validated in general hospitalised adult patients

82



BMI = Body mass index, MAC = Mid arm circumference, TST = Triceps Skinfold Thickness, MAMC = Mid arm Muscle Circumference, TLC = Total Lymphocyte Count

Tool (Lead author)



Number of

subjects

Number of

raters

Inter-rater

reliability

Number

of

subjects

Reference standard Assessor for tool

and reference

standard/ Blinding


OTHERS (in chronological order)

Screening Nutritional Profile (Hunt et al., 1985a)

Hospital adult

patients

(United States) Not evaluated Not evaluated

East Orange Nutrition Screening Form (Brown & Stegman, 1988)

Medical and

surgical patients

on admission

(United States)

Not evaluated

94 Subsequently received total

parenteral nutrition or referral

for dietary consultation Not specified

95% 89%

Nursing Nutritional Assessment Tool (Scanlan et al., 1994)

Hospitalised

patients

(United Kingdom) Not evaluated Not evaluated

Nutrition Risk Score (Reilly et al., 1995)

Hospitalised

patients on

admission

(United Kingdom)

20 2 Correlation: r = 0.91

(between dietitians)

r= 0.83 (between

dietitian and nursing

staff)

40 Nutritional Risk Index (NRIb)

and Clinical Impression

10 dietitians,

blinding not

specified

Correlation: r = 0.68

(NRIb)

r= 0.83 (clinical

impression)

Nutrition Risk Classification (Kovacevich et al., 1997)

Hospitalised

patients on

admission

(United States)

186 1 nurse

and 1

nutritionist

Inter-observer

agreement of nutrition

classification between

nurse and nutritionist

was 97.3% (p = 0.95)

56 Prealbumin levels Not specified who

retrieved the

prealbumin results,

blinding not

specified

84.6 62.7

83




Tool (Lead author)



Number

of

subjects

Number

of raters

Inter-rater

reliability

Number of

subjects


and reference

standard/ Blinding


Derby Nutritional Score (Goudge et al., 1998)

Hospital patients

(United

Kingdom) 70 5

Agreement

between

pairs of

nurses

(median

k=0.7)

73

Dietetic Assessment Scale based

on current actual weight,

percentage weight change, if any,

during the last 3 months, current

appetite and current dietary

intake.

1 nurse conducted

screening, 1

dietitian performed

reference standard,

blinding not

specified

Moderately good

agreement (kappa=0.6)

Nutrition Risk Check (Rawlinson, 1998)

Hospitalised

patients

(United

Kingdom)

Not evaluated Not evaluated

Nutritional Screening Tool (Scott & Hamilton, 1998)

(United

Kingdom) Not evaluated Not evaluated

Screening Sheet (Thorsdottir et al., 1999)

Hospital patients

from medical

and surgical

wards (Iceland)

Not evaluated 82

≥ 3 of these seven parameters

below reference value:

BMI ≤ 20 kgm-2, Albumin < 38

g/L, Total protein < 66 g/L

Prealbumin < 180mg/L

Haemoglobin < 130 g/L

(women) or < 118 g/L (men)

TLC < 1.8 x 109/L

TST & MAC <10th centile

1 dietitian and

nurses, blinding not

specified

69% 91%

84



Tool (Lead author)



Number

of

subjects

Number

of raters

Inter-

rater

reliability

Number

of

subjects

Reference standard Assessor for tool and

reference standard/

Blinding


Nutrition Assessment Score (Oakley & Hill, 2000)

Medical and

surgical wards

patients

(United Kingdom) Not evaluated 118

Dietetic Assessment Form: BMI < 20

kgm-2, MAC, TST , MAMC <15th

centile, weight loss ≥10%, Dietary

assessment, appetite, problems with

eating, mental/social conditions,

disease state

1 dietitian conducted

both the screening

and assessment at

the same sitting, not

blinded

First week

of study:

100%

Last 3

weeks of

study:

95.8%

First week

of study:

65%

Last 3

weeks of

study:

78.5%

Simple Screening Tool #1 & # 2 (Laporte et al., 2001a)

Hospitalised acute

care adult (<65 yrs

old) (Canada)

Not evaluated 54

At least 4 of these nutrition indicators

were abnormal: BMI, weight loss, TST,

SSF mid arm muscle area,

biochemical, dietary assessment and

physical examination

1 diet technician and

2 dietitians, blinding

not specified

33.3%

33.3%

81.3%

97.9%

Hospitalised acute

care elderly (≥65

yrs) (Canada)

Not evaluated 57

78.6%

76.7%

92.9%

83.7%

Nutrition Screening Tool (Burden et al., 2001)

Hospital patients

(Medical, surgical,

renal and elderly)

(United Kingdom) 100 2

95%

level of

agreeme

nt

100

One or more markers of BMI < 20

kgm-2, MAC <15th centile, weight loss

>10%, and 25% of energy intake on

the first day in hospital as compared to

estimated energy requirements

1 nurse conducted

screening, 1 dietitian

performed reference

standard, blinding

not specified

78% 52%

Nutrition Screening Tool (Weekes et al., 2004)

Hospitalised

patients to a

general medical

ward

(United Kingdom)

26 3 nurses

k = 0.66

(fair

agreeme

nt)

100

BMI 18.5–20.0 kg/m2 or 5–10% weight

loss in the previous 3–6 months

or nil by mouth for >5 days

or TSF, MAC, or

MAMC <5th centile with no weight loss

1 nurse & 1 dietitian,

blinded k = 0.717

(good

agreement)

Not

specified


85



Tool (Lead author)



Number of

subjects

Number of

raters

Inter-rater

reliability

Number

of

subjects


and reference

standard/ Blinding



Hospitalised

patients

(Netherlands)

47 Not

specified

k = 0.69

(between nurse

and nurse)

k = 0.91

(between nurse

and dietitian)

291 BMI < 18.5 kgm-2 and

unintentional weight loss ≥

5% in the last 6 months

Number of

assessors and

blinding not

specified

86% 89%

Nutrition Risk Index (Kyle et al., 2006)

Medical and

surgical

inpatients

(Switzerland)

Not evaluated 995 SGA 2 trained co-

workers, not

blinded

43% 89%

Nutritional Risk Screening 2002 (Kyle et al., 2006)

Medical and

surgical

inpatients

(Switzerland)

Not evaluated 995 SGA 2 trained co-

workers, not

blinded

62% 93%

Nutrition Screening Tool (Mirmiran et al., 2011)

Hospitalised

patients on

admission

(Iran)

150 2 nurses k = 0.68 & 0.74 414 BMI 18.5–20.0 kg/m2 or 5–

10% weight loss in the

previous 3–6 months

or decreased dietary

intake with <5% weight loss

in the previous 3–6 months

or TST, MAC, or

MAMC <5th centile with no

weight loss

1 nurse & 1

nutritionist, blinded

86.7% 61.7%


86


1.2.4 Reference Standard to Validate a Nutrition Screening Tool

Nutrition screening tools are often validated using nutrition assessment tools. For

example, Malnutrition Screening Tool (MST) has been validated against SGA in

several studies (Ferguson et al., 1999a; Ferguson et al., 1999b; Isenring et al.,

2006). Some components contained within a nutrition screening tool are also

utilised as part of assessment, for example components of weight loss and loss

of appetite are present in MST and Nutrition Risk Score (NRS) (both nutrition

screening tools) as well as in SGA (nutrition assessment tool) (Ferguson et al.,

1999a; Corish et al., 2004). Body mass index is required in Malnutrition Universal

Screening Tool (MUST), Nutrition Risk Score (NRS) and Mini Nutritional

Assessment - Short Form (MNA-SF) (Rubenstein et al., 1999; Corish et al., 2004;

Stratton et al., 2004). Charney (2008) suggested that nutrition assessment

continues the data gathering process initiated during nutrition screening

(Charney, 2008). Assessment allows the clinician to gather more information to

determine if there is indeed a nutrition problem, to name the problem, and to

determine the severity of the problem (Charney, 2008). It is recommended that

patients identified to be at nutritional risk have a nutrition assessment carried out

to determine if the patient is malnourished (Lochs et al., 2006).

Nutrition assessment is a comprehensive approach to determine the nutritional

status of individuals, whether well nourished or malnourished (American Dietetic

Association., 1994). Nutrition assessment is designed to systematically and

accurately identify those individuals with clinically significant malnutrition that

require nutrition intervention (Capra, 2007). It is also used to monitor and

evaluate outcomes of nutritional interventions (Feldblum et al., 2010). It involves

more in-depth data collection, usually including a combination of physical,

objective and biochemical data (Charney, 2008). Validity of nutrition assessment

tools is usually established against clinical outcomes (Table 1.3) or more definite

measurements such as body composition (Bannerman & Ghosh, 2000; Lawson

et al., 2001; Gupta et al., 2005; Norman et al., 2008b). ESPEN specified that

87


nutrition assessment should be conducted by “an expert clinician, dietitian, or

nutrition nurse” (Lochs et al., 2006).

In medical practice, screening tests such as mammogram and fecal occult blood

test are always validated against diagnostic tests, such as biopsy of breast tissue

and colonoscopy respectively (Wilhelm et al., 1986; Parente et al., 2009; Oxner

et al., 2012; Muinuddin et al., 2013). Similar to this concept, a nutrition screening

tool should always be validated against nutrition assessment which can provide a

diagnosis.

The decision on which nutrition assessment tool to validate a nutrition screening

tool can be based on these criteria:

• Able to diagnose malnutrition (refer to Table 1.2)

• Can be used for monitoring the progress of patients and effectiveness of

nutrition intervention (Beattie et al., 2000; Paton et al., 2004; Vermeeren et

al., 2004; Ravasco et al., 2005a; Norman et al., 2008a; Ha et al., 2010;

Paccagnella et al., 2010)

• Validated against clinical outcomes (refer to Table 1.3)

• Reliable (results repeatable) (refer to Table 1.8)

• Easy to use for dietitians

• Non-invasive for patients

• Inexpensive

Table 1.7 presents the various nutrition assessment tools, their components, and

compares them based on the above criteria. Subjective Global Assessment is the

only nutrition assessment tool able to fulfill all the criteria above and will be

discussed in the next section.

88


Table 1.7: Comparison of nutrition assessment methods to validate a nutrition screening tool

Nutrition assessment methods based on previous studies

stated in Table 1.2 Components

PROPOSED CRITERIA

Limitations

Dia

gnos

e m

alnu

triti

ona

Mon

itor

prog

ress

Valid

ated

b

Rel

iabl

ec

Easy

to u

se

Non

-inva

sive

Inex

pens

ive

MAMC (Bishop et al., 1981)

a) Mid arm circumference (MAC) b) Triceps skinfold thickness (TST) No Yes Yes No No Yes Yes

Skinfold callipers required Results skewed with untrained and inexperience staff Hassle of carrying callipers around Percentile chart and equations not validated for non-Caucasian

AMA / CAMA (Heymsfield et al., 1982)

Mid arm muscle circumference (MAMC) No Yes Yes No No Yes Yes

SGA (Baker et al., 1982a)

a) History of weight loss b) Changes in dietary intake c) Gastrointestinal symptoms d) Functional status e) Disease state affecting nutritional

requirements f) Muscle wastage g) Fat stores h) Ankle or sacral oedema or ascites

Yes Yes Yes Yes Yes Yes Yes Subjective assessment Requires trained and experienced staff to perform 7- Point SGA

(Churchill et al., 1996) Yes Yes Yes Yes Yes Yes Yes

PG-SGA (Ottery, 1994) Yes Yes Yes Yes No Yes Yes

The first part of the assessment needs to be completed by the patient. Literacy and understanding level may be a challenge for patients

Mini Nutritional Assessment (MNA) (Guigoz et al., 1996)

g) BMI h) Mid arm circumference i) Calf circumference j) Weight loss in pass 3 months k) Living independently vs. nursing home l) > 3 prescription drugs m) Presence of psychological stress/ acute

disease n) Mobility o) Neuropsychological problems p) Pressure sores / skin ulcers q) Number of full meals per day r) Frequency of protein foods consumption s) Frequency of fruits and vegetables t) Declining food intake in pass 3 months u) Beverages consumption per day v) Mode of feeding w) Nutritional problems as scored by patient x) Patients perception of his/her health

Yes Yes Yes Yes No Yes Yes

Lengthy questionnaire of 18 items takes time to complete Limited to the use in the elderly. Hence, need to use a different tool for younger adult patients

MAMC = Mid arm muscle circumference, MAC = Mid arm circumference, TST = Triceps skinfold thickness, AMA = Arm muscle area, CAMA = Corrected arm muscle area, SGA = Subjective Global Assessment, PG-SGA = Patient-generated Subjective Global Assessment, BMI = Body Mass Index, MNA = Mini Nutritional Assessment a.) Refer to Table 1.2, b.) Refer to Table 1.3, c.) Refer to Table 1.8

89


Table 1.7: Comparison of nutrition assessment methods to validate a nutrition screening tool

Nutrition assessment methods based on previous studies

stated in Table 1.2 Components

PROPOSED CRITERIA

Limitations

Dia

gnos

e m

alnu

triti

ona

Mon

itor

prog

ress

Valid

ated

b

Rel

iabl

ec

Easy

to u

se

Non

-inva

sive

Inex

pens

ive

Biochemical (Albumin / Prealbumin / TLC) (Doweiko & Nompleggi, 1991)

Blood test for serum albumin, prealbumin or Total Lymphocyte Count No Yes Yes No Yes No No

Invasive and costly – need blood test Results not immediately available and is marred by inflammation, illness and fluid balances Overdiagnosis of malnutrition (low specificity)

BMI (World Health Organisation, 1995)

a) Weight b) Height No Yes No Yes Yes Yes Yes

Missing data for patients unfit to be weighed Results inaccurate for subjects with fluid retention or dehydration. Cutoffs confounded by ethnicity.

Combined method s (Edington et al., 2000; Meijers et al., 2009)

BMI < 20 with either TST or MAMC below the 15th percentile or BMI ≤ 18.5 (age 18–65 y) or ≤20 (age >.65 y); or Unintentional weight loss (≥ 6 kg in the last 6 months or ≥3 kg in the last month); or No nutritional intake for 3 days or reduced intake for >10 days combined with a BMI of 18.5–20 (age 18–65 y) or 20–23 (age >65 y)

No No No No No Yes Yes Cutoff for malnutrition not standardised Not well accepted BMI has limitations mentioned above.

TLC = Total Lymphocyte Count, MAMC = Mid arm muscle circumference, MAC = Mid arm circumference, TST = Triceps skinfold thickness, BMI = Body Mass Index a.) Refer to Table 1.2, b.) Refer to Table 1.3, c.) Refer to Table 1.8

90


Subjective Global Assessment (SGA)

Subjective Global Assessment (SGA) is well accepted as an assessment tool in

clinical practice (Baker et al., 1982a; Detsky et al., 1987; Lochs et al., 2006).

Subjective Global Assessment was developed by Baker et al to predict outcomes

in surgical patients and the tool was first published in 1982 (Baker et al., 1982b).

This validated and widely used nutrition assessment tool involves evaluation of

weight and dietary intake changes, gastrointestinal symptoms, functional capacity,

metabolic stress level from disease state and physical examination for evidence of

fat depletion, muscle wasting and nutritional related oedema. There is no

numerical weighting or scheme for combining the history and physical

examination into SGA; instead a subjective assessment of nutritional status is

made (Baker et al., 1982a; Detsky et al., 1987; Ek et al., 1996). The final SGA

rank is based on the subjective weighting of these features to classify patients into

three categories (3-point): A = well nourished, B = moderately malnourished and

C = severely malnourished (Baker et al., 1982b).

Subjective Global Assessment has been regarded by ASPEN as the best nutrition

assessment tool and one of the only two tools (the other one being MNA)

recognised as an assessment tool (A.S.P.E.N. Board of Directors and the Clinical

Guidelines Taskforce., 2002; Mueller et al., 2011). It has been incorporated into

clinical practice guidelines as a tool for assessing nutritional status in acute care

setting by the Dietitians Association of Australia (DAA) and ESPEN (Lochs et al.,

2006; Watterson et al., 2009). It is an easy, non-invasive and inexpensive tool for

widespread use by trained clinicians or dietitians (Keith, 2008).

Table 1.8 presents validation studies carried out with SGA. Subjective Global

Assessment was initially validated against the clinical judgment of clinicians in a

blinded manner (Baker et al., 1982a; Detsky et al., 1984). Subsequent studies

tested it against various anthropometry, biochemical and functional parameters

(Hirsch et al., 1991; Norman et al., 2005; Devoto et al., 2006; Pham et al., 2007).

91


For consistency in results, a nutrition assessment tool has to be reliable. The SGA

has good reliability if carried out by experienced clinicians and dietitians

(Steenson et al., 2013). A recent review paper on the inter-rater reliability of SGA

presented 11 published studies that showed agreement level of between 74-91%

(kappa = 0.34-0.88) (Steenson et al., 2013). It has been proposed that good inter-

rater reliability in SGA can be achieved with training and standardised data

collection techniques (Hirsch et al., 1991; Ek et al., 1996).

Subjective Global Assessment has been widely accepted and used as a

diagnostic tool for malnutrition, to track clinical outcomes and as a reference

standard to validate nutrition screening tools (Keith, 2008; Makhija & Baker, 2008;

Steenson et al., 2013). Among all the nutrition assessment tools, Subjective

Global Assessment had the most number of studies that used it to diagnose

malnutrition and track clinical outcomes, which equates to prognostic validation of

the tool (refer to Table 1.3) (Baker et al., 1982a; Detsky et al., 1984; Middleton et

al., 2001; Bauer & Capra, 2003; Correia & Waitzberg, 2003; Gupta et al., 2005;

Kyle et al., 2006; Kubrak & Jensen, 2007). The results of studies using SGA

consistently indicated poorer survival, higher length of hospital stay and higher

hospitalisation costs among malnourished patients (Middleton et al., 2001; Correia

& Waitzberg, 2003; Gupta et al., 2005). Correia and Middleton found that patients

rated as malnourished (categories B or C) using SGA stayed in the hospital 1.5-

1.7 times longer than well-nourished patients (Middleton et al., 2001; Correia &

Waitzberg, 2003). Middleton followed 819 patients for 12 months and found that

the mortality rate for Australian malnourished patients (rated using SGA) was

three times higher than well-nourished patients (Middleton et al., 2001). Using the

same tool for nutrition assessment, there was a 60% increased cost of

hospitalisation for malnourished patients in a study conducted in 25 Brazilian

hospitals (Correia & Waitzberg, 2003).

Due to its good prognostic value for a range of clinical outcomes, SGA has been

widely used as reference tool for validating screening tools (Table 1.6). The

92


Malnutrition Screening Tool (MST), MUST, NRS-2002 and NRI have all been

validated against SGA (Ferguson et al., 1999a; Ferguson et al., 1999b; Middleton

et al., 2001; Bauer & Capra, 2003; Correia & Waitzberg, 2003; Kyle et al., 2006;

Kubrak & Jensen, 2007; Lawson et al., 2012). Since the original 3-point SGA was

created, a number of modified versions have been developed, including the 7-

point SGA and Patient Generated SGA (PG-SGA), which will be discussed next.

7-point SGA

One of the disadvantages of the original SGA which consists of a 3-point scale is

that small differences in nutritional status during follow-up cannot be detected. To

overcome this problem, Churchill et al expanded the scale to a 7-point scale for

use in the well-known CANUSA study carried out on 680 patients commencing

peritoneal dialysis (Churchill et al., 1996). The ratings for nutritional status were

expanded to range from 1 to 7, in which ratings of 1-2 signify severely

malnourished, 3-5 signify moderately malnourished and 6-7 signify well nourished

(Churchill et al., 1996). Therefore, the results of nutrition status as assessed by

the 7-point scale will always be aligned with the conventional SGA, i.e. well

nourished, moderately malnourished or severely malnourished. The CANUSA

showed that a one unit lower score in the 7-point SGA was associated with 25%

increased relative risk of death (Churchill et al., 1996). Since then, the 7-point

SGA has been used widely to determine the nutritional status of renal patients in

clinical settings as well as in research (McCann, 1999; Visser et al., 1999;

Campbell et al., 2007; Steiber et al., 2007).

Nutrition assessment needs to be on-going in order to detect subtle decline in

patients or to track the patient’s response to nutritional intervention. Therefore it is

important to use a nutrition assessment tool that can detect small changes in

nutritional status and which is not confounded by hydration status of the patient.

Some authors have speculated that the 7-point SGA scale may be more sensitive

in identifying small changes in patients’ nutritional status (Jones et al., 2004;

93


Campbell et al., 2007). The candidate has been using the 7-point scale on her

patients for the past 14 years and her anecdotal experience is that by using this

tool, dietitians are able to detect changes faster in patients who improve or

deteriorate especially within the same category of nutritional status. For example,

in the original SGA assessment, a patient who is rated as “B” (malnourished) may

take 4 months to improve to “A” (well nourished). In the 7-point SGA scale, a

malnourished rating can be 3, 4 or 5. If a patient improves from a rating of 3 to

rating 4 (although still regarded as moderately malnourished), this signifies that

the nutrition care plan is on track. Vice versa, when a patient deteriorates across

the ratings, this can be picked up faster with the expanded 7-point SGA scale and

the nutrition intervention plan adjusted accordingly. There are no studies thus far

to support this opinion. However it is interesting that Campbell’s study showed an

increase in mean BCM from the lower rating of 3 to the highest rating of 7

(Campbell et al., 2007). The increase had a 2-stage pattern, whereby there was a

linear increase from SGA rating 3 to 5 and plateau from rating 5 to 7. This showed

that there was actually a body composition difference between the ratings (3, 4

and 5) within the same nutritional status (SGA B). To date the use of 7-point SGA

has been limited to renal patients.

To support the use of 7-point SGA in monitoring nutritional outcomes in an

intervention programme for malnourished patients, we conducted a study to

determine if 7-point SGA is able to detect small nutritional changes faster than the

conventional SGA. We have validated that the 7-point SGA scale is indeed more

time-sensitive in identifying small changes in patients’ nutritional status. That work

and research paper will support the use of 7-point SGA to monitor the nutritional

outcome of patients after discharge from the hospital and is not part of this

research programme (attached in Appendix E).

94


Patient-generated SGA (PG-SGA) The Patient-generated Subjective Global Assessment (PG-SGA) was adapted

from SGA, specifically for use with oncology patients (Ottery, 1994; 1996). The

rationale for doing this was because SGA lacked sensitivity to detect

improvements in nutritional status observed over a short hospital admission. The

PG-SGA has all the components of the original SGA but requires more detailed

information. This tool is designed in a checkbox format for patients to complete

the first part of the assessment, which contains the history of weight change,

changes in food intake, gastrointestinal symptoms and functional activities. The

second part on medical condition, metabolic stress, muscle wastage, fat depletion

and oedema is completed by a healthcare professional. PG-SGA incorporates a

numerical score for each section, which is totalled to assist the assessor decide

on the next appropriate course of action.

The PG-SGA has been validated in oncology (Bauer et al., 2002; Isenring et al.,

2003a) and haemodialysis (Desbrow et al., 2005) patients and shown to have

good sensitivity, specificity and inter-rater reliability compared to the original SGA.

All the above studies were carried out in Australia. In a study on 71 oncology

patients admitted to an Australian private tertiary hospital, the PG-SGA score had

a sensitivity of 98% and a specificity of 82% when compared to SGA as reference

standard (Bauer et al., 2002). A prognostic validity study on PG-SGA was carried

out on 73 patients admitted to an acute stroke unit in an Australian private hospital

(Martineau et al., 2005). In this study, patients diagnosed as malnourished using

PG-SGA had longer lengths of stay (13 days vs. 8 days), increased complications

(50% vs. 14%), increased frequency of dysphagia (71% vs. 32%) and enteral

feeding (93% vs. 59%) (Martineau et al., 2005).

A limitation of PG-SGA is that the first part of the assessment is designed to be

completed by the patient. In Singapore, literacy level may be a challenge for some

patients in completing the form. On the other hand, the use of nurses to carry out

95


the first part of PG-SGA may be resource-intensive and not suitable for use in

Singapore hospitals. Another limitation of PG-SGA is that it is not always able to

achieve the same results as the conventional SGA (Bauer et al., 2002; Desbrow

et al., 2005).

Mini Nutritional Assessment (MNA) Another well-recognised nutrition assessment tool is the MNA (Guigoz et al.,

1994; Guigoz et al., 1996). It consists of 18 items which are grouped into

anthropometric measurements, global evaluation of independent living,

medication intake, acute disease, psychological problems, mobility and pressure

ulcers, dietetic assessment on the number of full meals consumed per day, mode

of feeding, appetite, consumption of protein, vegetables, fruits and fluid, subjective

assessment of health status and whether the patients think they have malnutrition

(Guigoz et al., 1994; Guigoz et al., 1996). The MNA is based on a scoring system

to classify individuals into 3 categories: a) ≥24 points: normal nutrition status, b)

17-23.5 points: borderline status/at risk, c) <17 points: malnutrition. It has been

widely used to assess the nutrition status of the elderly (Compan et al., 1999;

Gazzotti et al., 2000; Thomas et al., 2002; Visvanathan et al., 2004; Neumann et

al., 2005; Feldblum et al., 2007; Bauer et al., 2008; Tsai et al., 2009; Vanderwee

et al., 2010; Pereira Machado & Santa Cruz Coelho, 2011) It has also been

extensively validated and is able to predict outcomes in the older adults (Persson

et al., 2002; Hudgens et al., 2004; Kagansky et al., 2005; Neumann et al., 2005;

Charlton et al., 2007; Bauer et al., 2008; Cereda et al., 2008a; Wikby et al., 2008;

Chan et al., 2010; Charlton et al., 2012; Tsai et al., 2013). However MNA’s use

has been limited to the elderly population and evidence of its validity in other age

groups has not been established. Other limitations of MNA are its lengthy

questionnaire and the requirement of patient’s BMI which may lead to difficulty in

completing the assessment on some patients. In a study of hospitalised geriatric

patients, MNA could only be completed in 66% of patients (Bauer et al., 2005).

96


Due to the above reasons, MNA was deemed not suitable for use as reference

standard for this research programme which encompasses all adult age groups.

Summary of Reference Standard to Validate Nutrition Screening Tool From the literature review, there are various methods for nutrition assessment.

However, SGA is the most widely used and accepted assessment tool to

determine nutritional status and validate nutrition screening tools in adult

hospitalised patients due to its good prognostic value for a range of clinical

outcomes. It is non-invasive, inexpensive and has also been shown to be reliable

and easy to use by dietitians. It can be used across the adult age range. For

monitoring the progress of patients, the 7-point scale SGA is able to detect small

nutritional changes over shorter periods of time without differing from the final

results of the conventional SGA.

97


Table 1.8: Studies on reliability and validity of Subjective Global Assessment and other modified versions of SGA Tool

(Lead author) Participants,

Country Reliability Relative validity

Number

of

subjects

Number

of raters

Inter-rater

reliability

Num

ber of

subje

cts

Reference standard Assessor for

tool and

Blinding


SGA (Baker et al., 1982a)

Surgical patients

(before surgery)

(Canada)

59 2 81% 48

Albumin, Total lymphocyte

count, Transferrin, % actual lean

BW/ideal lean BW, % actual

BW/ideal BW, %body fat/BW

2 assessors,

blinded

Significant correlation between all

reference standard except total

lymphocyte count and transferrin

SGA (Detsky et al., 1984)

Surgical patients

(before surgery)

(Canada)

59 2 k = 0.72 59 Ability to predict infection 2 assessors,

blinded 82% 72%

SGA (Hirsch et al., 1991)

Gastroenterology

patients within 4

days of admission

(United States)

175 2 79% 139

Weight, mid arm circumference,

triceps skinfold, and serum

albumin

Not

applicable

Significant difference in

measurements between well

nourished, moderately malnourished

and severely malnourished

SGA (Covinsky et al., 1999)

Patients (>70years)

with length of stay

at least 3 days and

admitted to general

medical unit

(United States)

21

2,

Internist

and

nurse

k = 0.71 Not evaluated

SGA (Scolapio et al., 2000)

Patients with

cirrhosis

(United States)

15

2,

Dietitian

&

physician

>90% 15 Respiratory quotient, BMI,

Albumin, TSF, MAMC, CHI

3 assessors,

(2 dietitians

and 1

physician), not blinded

Significant correlation between

respiratory quotient, albumin and

CHI with SGA

SGA = Subjective Global Assessment, SGA A = Well nourished, SGA B = moderately malnourished, SGA C = severely malnourished, BMI = Body mass index, BW= Body weight, TST = Triceps Skinfold Thickness, MAMC = Mid arm muscle circumference, MAC = Mid arm circumference CRP = C-reactive protein, PCR = Protein Catabolic Rate, k = kappa

98


Table 1.8: Studies on reliability and validity of Subjective Global Assessment and other modified versions of SGA (continued)

Tool (Lead

author)



Number

of

subjects

Number of

raters

Inter-rater

reliability

Number

of

subjects


and Blinding


SGA (Sacks et al., 2000)

Residents (≥65

years) admitted to

long-term care

facility

(United States)

53 2,

Pharmacists

85%,

k = 0.75 53

Readmission,

Mortality up to 3 months

after SGA, height, actual

weight, usual weight, %

usual weight, Ideal

weight, % ideal weight,

BMI, Albumin,

Cholesterol

2 pharmacists,

blinded

Hospital

Readmission=

50%

Mortality= 75%

Hospital

Readmission=

80%

Mortality= 84.4%

Significant difference between well

nourished, moderately malnourished

and severely malnourished for actual

weight, % usual weight, % ideal

weight and , BMI.

SGA (Duerksen et al., 2000)

Patients

(>70years)

admitted to

geriatric and

rehabilitation units

(Canada)

87

2,

Physicians

73.6%,

k = 0.48 87

Hemoglobin, Albumin,

Cholesterol,

Lymphocyte, TST,

Subscapular skinfold,

MAMA, BMI, Grip

strength

3 assessors, (1

medical student

and 2 physician),

blinded

Significant correlation between SGA

and TST, subscapular skinfold and

BMI.

Grip strength and laboratory data did

not correlate significantly with clinical

SGA.

SGA (Duerksen, 2002)

Any available

patients

(Canada)

30-37

60-75

medical

students and

dietitians

78%,

k = 0.51 (not

blinded)

65%,

k = 0.34

(blinded)

Not evaluated

SGA = Subjective Global Assessment, SGA A = Well nourished, SGA B = moderately malnourished, SGA C = severely malnourished, BMI = Body mass index, BW= Body weight, TST = Triceps Skinfold Thickness, MAMC = Mid arm muscle circumference, MAMA = Mid arm muscle area, CRP = C-reactive protein, CHI = creatinine height index, k = kappa

99



Tool (Lead author)

Participants, Country Reliability Relative validity

Number

of

subjects

Number

of raters

Inter-rater

reliability

Number

of

subjects

Reference standard Assessor

for tool and

Blinding


SGA (Nursal et al., 2005a)

Hospitalised patients

except pregnant, had

psychiatric conditions,

and intensive care unit

patients

(Turkey)

2199

2,

Dietitian

and

nurse

k = 0.88

(p<0.001)

Not evaluated

SGA (Devoto et al., 2006)

Inpatient at Medicine,

Neurology, Long-term

care and Rehabilitation

wards (Italy)

Not evaluated 108 Detailed Nutritional

Assessment

Not

specified 77% 84%

SGA (Pham et al., 2007)

Patients admitted for

elective major

abdominal surgery

(Vietnam)

Not evaluated 274

BMI

Weight, Weight loss, BMI,

Skinfold (TST), MAMC,

Albumin, Handgrip strength

Serum total protein,

Haemoglobin, CRP,

Lymphocytes

Not

specified

k = 0.670 (good agreement)

Significant differences between SGA A

& B for Weight, Weight loss BMI,

Skinfold (TST)

MAMC, Albumin & Haemoglobin

Significant differences between SGA B

& C for all measures tested except for

CRP and lymphocytes

SGA (Baccaro et al., 2007)

Hospitalised patients to

an internal medicine

service

(Argentina)

75 5,

Physicians

Kappa=

0.75 Not evaluated

SGA = Subjective Global Assessment, SGA A = Well nourished, SGA B = moderately malnourished, SGA C = severely malnourished, BMI = Body mass index, BW= Body weight, TST = Triceps Skinfold Thickness, MAMC = Mid arm muscle circumference, CRP = C-reactive protein, k = kappa

100



Tool (Lead author)


Number of

subjects

Number

of

raters

Inter-rater

reliability

Number

of

subjects

Reference

standard

Assessor for tool and

Blinding


7-point SGA (Visser et al., 1999)

Haemodialysis and

peritoneal dialysis patients

(Netherlands)

22 4 k = 0.72

k = 0.88 22

BMI,

Mid arm

circumference,

Mid arm

muscle

Circumference,

Serum

albumin,

Prealbumin

4 nurses, blinding not

specified

Correlations with 7point

SGA scale :

• BMI (r = 0.79, p <

0.001), % fat (r = 0.77,

p <0.001),

• Mid arm

circumference (r =

0.71, p < 0.001)

• Prealbumin (r = 0.60,

p = 0.004).

Lower correlations were

found with mid arm

muscle circumference

and serum albumin.

7-point SGA (Steiber et al., 2007)

Haemodialysis patients

(Canada and United States)

76 (inter-

rater)

111 (intra-

rater)

54

k = 0.5,

Spearman’s

Rho=0.7

k = 0.7

Spearman’s Rho

= 0.8

154 BMI

Albumin

54 dietitians , blinding

not specified

Statistical difference in

mean BMI (p<0.05) and

albumin (p<0.001) across

the 5 categories of SGA

SGA = Subjective Global Assessment, BMI = Body Mass Index , k = kappa

101



Tool (Lead author)


Number

of

subjects

Number

of raters

Inter-rater

reliability

Number of

subjects

Reference standard Assessor for tool and

Blinding


Patient-Generated SGA (Bauer et al., 2002)

Oncology Inpatient

(Australia) Not evaluated 71 SGA 1 assessor, not blinded

98%

82%

Patient-Generated SGA (Desbrow et al., 2005)

Haemodialysis

inpatients (Australia) Not evaluated 60

SGA

Dietitian, research

student and examiner

(blinding not specified)

83% 92%

Dialysis Malnutrition Score (quantitative and modified from SGA) (Kalantar-Zadeh et al., 1999)

Dialysis patients

(United States) 41

2,

Dietitian

and

physician

k = 0.83 41

Transferrin, Albumin,

Total protein,

Cholesterol,

Triglyceride, Creatinine,

Haematocrit,

Lymphocyte count,

MAC, MAMC, TST,

Biceps, BMI, URR, PCR

1 assessor, not blinded No correlation between the conventional SGA and any

other parameter.

Quantitative SGA (Q-SGA) and Modified Quantitative SGA (MQ-SGA) ((Nursal et al., 2005b)

Hospitalised patients

except pregnant, had

psychiatric conditions,

and intensive care unit

patients

(Turkey)

Not evaluated 2197 SGA 1 dietitian, not blinded

Q-SGA: 90%

MQ SGA:

90.9%,

Q-SGA:

67%

MQ SGA:

85.6%,

SGA = Subjective Global Assessment, BMI = Body Mass Index

102


1.2.5 Compliance with Nutrition Screening

For a nutrition screening tool to be effective, it must be completed fully and

accurately. However, the current literature reveals high rates of non-compliance

for nutrition screening. In a large Nutrition Day survey on 1217 organisational

units from 325 hospitals in 25 European countries and Israel (n = 21,007 patients),

a screening routine existed for only 52 % (range 21 - 73%) of the units surveyed

(Schindler et al., 2010). Self-reported surveys among healthcare professionals

indicate that routine screening for nutritional risk on admission is present in 13-

78% of the departments or institutions surveyed (Rasmussen et al., 1999; Mowe

et al., 2006; Lindorff-Larsen et al., 2007; Persenius et al., 2008; Ferguson et al.,

2010). In a survey on 68 healthcare institutions in Australia, 78% of the

respondents reported that nutrition screening occurs at their institutions (Ferguson

et al., 2010). However, out of those which had a nutrition screening process in

place, only half reported that all or almost all of their patients were screened

(Ferguson et al., 2010). In another study, Mowe et al. (2006) conducted a survey

by mail on the nutrition screening practices of 1753 doctors and 2759 nurses in

Denmark, Sweden and Norway. When asked if nutrition screening on admission

was carried out as a standard procedure, the results differed significantly between

the countries with a ‘yes’ response of 40%, 21% and 16% from Denmark, Sweden

and Norway respectively (Mowe et al., 2006).

Specifically, there are a number of studies published on the compliance rate with

various nutrition screening tools (Table 1.9). Of the 15 studies found in the

literature, 4 were published as abstracts (Wong & Gandy, 2008; Voyce & Seager,

2009; Wong et al., 2009; Joyce et al., 2011) with limited information. The

incompletion rates of nutrition screening in Australia and Europe range from 28%

to 97% (Raja et al., 2008; Wong & Gandy, 2008; Neelemaat et al., 2011b; Geiker

et al., 2012). High levels of missing data especially on disease severity were

found in MUST (Neelemaat et al., 2011b). In addition, 25% of the patients had

incomplete data on weight, height and/or weight loss (Neelemaat et al., 2011b)

103


and 69% had no data on BMI (Toumi & Lawson, 2011). In a different study on

NRS 2002, 76% of the 2393 patients audited were not screened for nutritional risk

at all during their hospitalisation (Geiker et al., 2012). All the studies presented in

Table 1.9 except one (Geiker et al., 2012) did not look at whether the nutrition

screening was being completed correctly. Geiker et al. (2012) found that 92% of

the patients screened with NRS 2002 were either not assessed within 24 hours

from admission or had their nutritional status underestimated (Geiker et al., 2012).

Failure to achieve accurate and complete nutrition screening will affect the final

score allocated to a patient, which may result in a malnourished or at risk patient

not being referred for nutritional intervention.

To complete the process of nutrition screening, any patient identified from

screening to be malnourished or at risk of malnutrition should be referred to the

dietitians to receive a full nutrition assessment and intervention (American Dietetic

Association., 1994; Lochs et al., 2006; Joint Commission International, 2008). The

incidence of under-treatment of malnutrition is increased when patients screened

to be at risk are not referred to, evaluated and/or monitored by a nutrition-trained

professional. The incidence of at risk patients not referred to the dietitians ranges

from 16% to 66% (refer to Table 1.9). Kondrup et al (2002) showed that only 47%

of patients identified as at nutritional risk using NRS 2002 had a nutrition plan

implemented, and of these only 30% had dietary intake and/or body weight

monitored (Kondrup et al., 2002). In a study by McWhirter and Pennington (1994),

up to 70% of malnourished patients were not provided with any form of nutritional

intervention (McWhirter & Pennington, 1994).

The literature search yielded limited studies on strategies to improve the

compliance of nutrition screening, which are mostly confined to staff training. Two

studies showed that staff training was able to improve the completion rates of

MUST from 54% to 67% (Wong & Gandy, 2008) and 37% to 55% (Raja et al.,

2008), although the end results were still less than desirable. Similarly, Keller

(2007) found that training was essential for the success of nutrition screening in

104


community-dwelling older adults in Canada (Keller et al., 2007). The paper

reported on the issue of building capacity for nutrition risk screening among the

elderly in the community and did not report on whether the project had led to

improvement in the quality and take-up rate of screening. The author indicated

that the time lag between training and implementing screening should be as short

as possible. In addition, the content and depth of training is beneficial if

individualised to the level of expertise of the administrator (Keller et al., 2007).

Bailey (2006) reported on the compliance of nurses to nutrition screening after

implementation of MUST and training in a tertiary hospital in UK. The study

showed contrasting results in different wards (Bailey, 2006). Two wards

demonstrated good initial screening rates (87% and 73%), but the results

dwindled to 35% and 33% by the third audit cycle. Another ward started with

screening rate of 16% and achieved 32% by the third audit cycle. After refresher

training sessions were provided, the screening rates improved in one ward to 94%

but deteriorated to 16% in another ward (Bailey, 2006). This demonstrates the

challenges of implementing nutrition screening and sustaining good screening

rates.

Summary of Issues on Compliance with Nutrition Screening

Literature review indicates that compliance to nutrition screening is poor and

strategies to improve the compliance rate and sustain the results are needed.

Other than staff training, no published study has described the use of quality

improvement tools to facilitate improvements in the compliance to nutrition

screening and its referral process. It is important to conduct audit and process

evaluation of implemented nutrition screening tools as part of quality assurance to

improve the compliance rate to nutrition screening and to ensure that

improvements are sustained over time. An audit of this nature can identify gaps in

implementation as a precursor to improving the nutrition screening process, the

quality of the tool and staff behaviour. Quality improvement tools may be able to

105


determine the root causes of non-compliance, which when effectively addressed

will lead to substantial improvement and sustain the results.

106

Malnutrition in hospitalised patients and clinical outcomes: A missed opportunity

Table 1.9: Non-compliance and error rates with various nutrition screening tools in hospitalised adult patients (sorted by countries)

Country (Author, Year) N Target Nutrition

Screening Tool

Non-Compliance Rate Incompletion rate

(%) Error rate / At risk patients not

referred (%) United Kingdom (Cooper, 1998) 48 Trauma inpatients Nutrition Checklist 33% 12% of at risk patients not referred to

dietitians

United Kingdom (Bell, 2007) 100

Medical emergency and surgical elective inpatient

admitted ≥ 7 days

Name of tool not mentioned

78% (surgical patients)

70% (medical patients)

Not specified

United Kingdom (Wong & Gandy,

2008)

432 Inpatient admitted ≥ 72hours MUST

46% (Audit in 2005) Not specified

392 33% (Audit in 2007) Not specified

United Kingdom (Voyce & Seager,

2009) 301 Inpatient admitted ≥ 48hours MUST 69%

92% of those screened were not done within 48 hours of admission

33% of at risk patients not referred to dietitians.

United Kingdom (Lamb et al.,

2009) 328 Inpatient aged > 16 years

admitted ≥ 24hours MUST 31% 55% of at risk patients not referred to dietitians

United Kingdom (Wong et al.,

2009) 81

Spinal injury inpatient aged 18-80 years admitted ≥

72hours

SNST 40% Not specified

United Kingdom (Joyce et al.,

2011) 140 Cardiac and cardiothoracic

inpatients NST

86%

81% had no BMI 66% of at risk patients not referred to

dietitians

United Kingdom (Toumi & Lawson,

2011) 48 Inpatient admitted ≥ 3 days

Weight, BMI and unintentional weight loss

64% had no weight, 69% had no BMI,

52% had no information on weight

loss

Not specified

MUST = Malnutrition Universal Screening Tool, SNST = Spinal Nutrition Screening Tool, NST = Nutritional Screening Tool, BMI = Body Mass Index, NHS QIS = National Healthcare System Quality Improvement Scotland, NRS 2002 = Nutritional Risk Screening 2002, MST = Malnutrition Screening Tool, SNAQ = Short Nutritional Assessment Questionnaire

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Table 1.9: Non-compliance and error rates with various nutrition screening tools in hospitalised adult patients (sorted by countries) (continued)

Country (Author, Year) N Target Nutrition

Screening Tool

Non-Compliance Rate Incompletion rate

(%) Error rate / At risk patients not

referred (%) Australia

(Middleton et al., 2001)

819 Inpatients admitted to 2 hospitals

Name of tool not mentioned Not specified

64% of malnourished patients were not identified by the screening tool and

referred to the dietitian

Australia (Raja et al., 2008)

47 Inpatient admitted ≥ 24hours in 4 wards

MST 96% (Audit 1)

Not specified 58 97% (Audit 2) 71 MUST 63% (Audit 1) 64 45% (Audit 2)

Australia (Porter et al.,

2009) 46 Inpatient admitted ≥

24hours in 2 wards MUST 39% (Ward A) 83% (Ward B) Not specified

Australia (Gout et al., 2009) 275 Inpatients admitted to a

public tertiary hospital Name of tool not

mentioned Not specified 64% of malnourished patients were not referred to the dietitian.

Denmark (Rasmussen et

al., 2004) 590

Inpatients admitted under 15 medical and surgical

department from 12 hospitals

NRS 2002

92%

86% of at risk patients did not have a nutrition plan documented

Denmark (Geiker et al.,

2012) 2393 Inpatient admitted in

September 2008 NRS 2002 76% 92% not assessed within 24hrs from

admission or had an underestimation of nutritional status

Netherlands (Neelemaat et al.,

2011b) 275 Adult inpatients ≥ 18 years

old

MUST MST

NRS 2002 SNAQ

39% 30% 28% 28%

Not specified

MUST = Malnutrition Universal Screening Tool, SNST = Spinal Nutrition Screening Tool, NST = Nutritional Screening Tool, BMI = Body Mass Index, NHS QIS = National Healthcare System Quality Improvement Scotland, NRS 2002 = Nutritional Risk Screening 2002, MST = Malnutrition Screening Tool, SNAQ = Short Nutritional Assessment Questionnaire

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1.3 INTERVENTIONS FOR PATIENTS WITH MALNUTRITION

The high prevalence and poor outcomes of hospital malnutrition are well

established, including longer length of hospital stay, higher mortality rate and

greater hospitalisation costs (Naber et al., 1997; Braunschweig et al., 2000;

Edington et al., 2000; Correia & Waitzberg, 2003) (see sections 1.1.2 and 1.1.4).

There is a need for hospital care to identify individuals at nutrition risk and put in

place a system to help improve the nutritional status of these patients. Nutrition

screening alone is insufficient to achieve beneficial effects and more research is

needed to explore interventions that will improve patient outcomes (Weekes et

al., 2009).

Possible ways to improve the outcomes of malnourished patients are to raise the

awareness of malnutrition amongst healthcare workers, and to put in place an

action plan that facilitates early identification of malnourished or at risk patients

so that appropriate medical nutrition therapy and adequate follow-up care can be

provided (Kruizenga et al., 2005b; O'Flynn et al., 2005).

The protocol for the management of malnourished patients needs to be

streamlined and evidence-based. The American Dietetic Association, recently

renamed as the Academy of Nutrition and Dietetics, has a general framework for

nutrition care process (Lacey & Pritchett, 2003). Based on this framework,

Campbell et al (2008) and Lim et al (2012) have published nutrition intervention

protocols for use in their studies on chronic kidney disease and haemodialysis

patients (Campbell et al., 2008; Lim, 2012). The results of these interventional

studies showed improvement in energy intake and nutritional outcomes for

patients (Campbell et al., 2008; Lim & Lye, 2012). However a nutrition care

process specifically for malnourished patients has not yet been developed.

Hence, a nutrition care process for the identification and management of

malnourished patients was developed based on the above protocols and the

candidate’s clinical experience (Figure 1.5).

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Figure 1.5: Nutrition Care Process for Malnutrition

Adapted from: Lacey 2003, Campbell 2008, Lim 2012 (Lacey & Pritchett, 2003; Campbell et al., 2008; Lim, 2012; Lim & Lye, 2012); American Dietetic Association (ADA), Oncology evidence-based nutrition practice guideline, Chicago (IL): American Dietetic Association (ADA), 2007 Oct; American Dietetic Association, Chronic kidney disease evidence-based nutrition practice guideline, Chicago (IL): American Dietetic Association; 2010 Jun. http://guideline.gov/content.aspx?id=23924&search=Renal+function+study

Nutrition Assessment and Diagnosis • Medical history and relevant laboratory tests, including biochemistry • Nutrition-focused assessment, including:

o Anthropometric data o Biochemistry o Detailed diet history leading to estimates of current macro and micronutrient intake,

especially calorie and protein intake o Subjective assessment of nutritional status using Subjective Global Assessment (SGA) o Physical activity o Psychosocial and economic factors impacting on nutrition o Readiness to change

Intervention • Individualised prescription for medical nutrition therapy

o Calculate nutrient requirements, including caloric and protein requirements. o Determine deficits in nutrient intake by comparing current intake with requirements. o Provide strategies to increase caloric, macro and/or micronutrient intake via diet o Prescription of supplements (as required) if is anticipated that modification in diet alone

is not able to meet requirement o Initiation of tube feeding nutrition support if oral nutrition support fails) or parenteral

nutrition if the gut is not working or there is contraindication to feed enterally • Self-management and family education

o Education on identifying macro and/or micronutrients o Recipe modification

• Behavioural interventions • Develop goals and set targets

Monitoring and Evaluation (Reassessment and Follow-up) • Anthropometry • Biochemistry • Dietary intake, including compliance with any supplements prescribed • Subjective Global Assessment • Behavioural change • Reinforce advice and provide further strategies for change if required

Expected outcomes • Body weight, muscle and fat stores improved • Biochemistry within expected range • Macro and micronutrient intake improved • Improvement in overall nutritional status or Subjective Global Assessment • Improved clinical outcomes i.e. length of stay, readmission, infection, quality of life,

survival rates

Nutrition Screening • Screen using a valid, reliable, quick, simple, effective and cost-efficient tool • Establish referral process for ‘at risk’ patients

110

http://guideline.gov/content.aspx?id=23924&search=Renal+function+study�


1.3.1 Nutrition Support for Malnourished Patients

The first line of treatment for malnourished patients is to increase nutrient intake

using food-based approach or through food fortification (Thomas, 2001). If

dietary intake is not able to meet requirements, oral supplementation is the next

line of treatment, followed by tube feeding and finally, if the gut is not working

and there is contraindication to feed enterally, parenteral nutrition can be

explored (Thomas, 2001).

Many studies have shown that patient outcomes can be improved with adequate

nutrition support (Kaminski, 1988; Otte et al., 1989; Beattie et al., 2000; Bourdel-

Marchasson et al., 2001; Isenring et al., 2003b; Isenring et al., 2004; Paton et al.,

2004; Smedley et al., 2004; Norman et al., 2008a; Ha et al., 2010; Paccagnella et

al., 2010). There are three Level I studies on nutrition support for malnourished

patients according to the NHMRC (National Health and Medical Research

Council, 2009) criteria. A Cochrane review consisting of 36 studies (n = 2714)

compared the effect of nutritional counselling to improve food-based nutrient

intake and supplements on the clinical and nutritional outcomes in malnourished

patients (Baldwin & Weekes, 2008). In the 2008 Cochrane review, the authors

concluded that a combination of nutritional counselling plus supplements is more

effective than supplements or dietary advice alone (Baldwin & Weekes, 2008).

Their recent review on 2123 participants stated that dietary counselling given

with or without supplements is effective at increasing the nutritional intake and

weight of patients (Baldwin & Weekes, 2012). The latter review reinforced that

individualised dietary counselling is the mainstay in helping malnourished

patients improve (Baldwin & Weekes, 2012).

A systematic review of 32 RCT papers (n=2286) on oral and enteral

supplementation showed that routine supplementation improved nutritional

indices (Potter et al., 1998). In the review paper, 17 out of the 32 trials reported

changes in anthropometric measures compared to control group. The treatment

group receiving routine nutritional supplementation showed consistently

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improved changes in body weight and anthropometry compared with controls;

weighted mean difference 2.06% (95% CI: 1.63% to 2.49%) and 3.16% (94% CI:

2.43% to 3.89%) respectively. The benefits of supplementation were not

restricted to particular patient groups (Potter et al., 1998).

Milne et al. (2009) reviewed 62 randomised and quasi-randomised controlled

trials of oral protein and energy supplementation in older people, excluding those

recovering from cancer treatment or in critical care. They concluded that with the

10,187 randomised participants, supplementation produced a small but

consistent weight gain (mean difference for percentage weight change = 2.2%,

95% CI 1.8 - 2.5), in older people (≥ 65 years old) who were undernourished

(Milne et al., 2009).

In another review paper of 84 studies on patients with chronic diseases in the

community (45 randomized, 39 non-randomized, n=2570), oral nutritional

supplementation had a positive effect on body weight and functional status such

as improved muscle strength and walking distance (Stratton & Elia, 2000). In

addition, there was a reduction of falls and increased ability to perform activities

of daily living in older adults. Besides the review papers, a meta-analysis of five

randomised controlled trials on 1224 older adult patients showed that oral

nutritional supplementation significantly reduced the risk of developing pressure

ulcers by 25% (Stratton et al., 2005).

In summary, there is a large and growing body of evidence to show that nutrition

support is effective and leads to improved nutritional status and clinical outcomes

in malnourished patients. For this reason, the mode (oral diet, tube feeding or

parenteral nutrition) and content (nutrient content, diet counselling or

supplements) of nutrition support will not be the focus of the PhD research.

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1.3.2 Post-discharge Follow-up of Malnourished Patients

The nutritional status of patients malnourished on admission often worsens

during the hospital stay, with a cumulative decline in status associated with

repeated readmissions (McWhirter & Pennington, 1994; Braunschweig et al.,

2000; Norman et al., 2008b; Cansado et al., 2009). This is, at least in part,

because the short length of stay of most inpatients limits the potential impact of

inpatient nutrition interventions that typically include nutrition supplements,

dietary fortification and patient education. Outpatient dietetic follow-up post-

discharge is commonly arranged in an attempt to extend the time frame and

potential effectiveness of these interventions (Kirkland et al., 2013). However,

the issue of patients becoming lost to follow-up is common, with a dropout rate

ranging from 54-58% of total dietetic outpatient attendances (Gallagher, 1984;

Finucane et al., 2007). A literature search yielded four studies that looked at

dietetics follow-up rate (Table 1.10). Only one small study focused on follow-up

rates of malnourished patients. Van Bokhorst-de van der Schuren et al. (2005)

observed that a dietitian saw only 54% of malnourished patients during

admission. Out of these, only 23% were followed-up by a dietitian after

discharge (van Bokhorst-de van der Schueren et al., 2005).

As discussed in the preceding section (1.3.1), dietary fortification and

counselling are often used as a first-line intervention for treating malnutrition in

the hospital. However, the effect of continuing care beyond hospital walls for

malnourished patients discharged from the hospitals has not yet been

thoroughly explored. The evidence base for this practice is weak and should be

addressed with well-designed trials that assess clinically relevant outcome

measures and costs.

At National University Hospital in Singapore, malnourished inpatients referred to

dietetics are given an appointment as part of discharge planning to come back

to the outpatient dietetic clinic for follow-up. However the candidate’s anecdotal

experience (which would be verified by data collection as part of this thesis) was

that most of these patients did not come back to the clinic for follow-up. This

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was despite the fact that patients or caregivers were given reminders either by

an appointment letter sent to their home address or short messaging system via

mobile phone (according to their preference indicated in the hospital registration

system) two weeks before the appointment. Possible reasons for patients failing

to attend these appointments include prolonged waiting time, emotional state of

patients, patients too weak to come to clinic, unawareness of the importance of

nutrition support and the consequences of malnutrition, perception that nutrition

support was not useful, costs, transport problems and not wanting to cause

inconvenience to family members.

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Table 1.10: Studies on follow-up attendance rate of patients seen by dietitians Lead Author,

Year Participants (Country) n Attendance/Follow-up Rate at Outpatient Dietetics Clinic Methods to increase follow-up rate Duration of follow-

up/ observation

(Gallagher, 1984)

New outpatients referred to dietitians

(United Kingdom) 209

46% (out of 61 Diabetic outpatients)

42% (out of 117 Weight reduction outpatients) 8% (other than above)

No specific method employed for this descriptive study 12 months

(van Bokhorst-de van der

Schueren et al., 2005)

Malnourished inpatients discharged from hospital

(Netherlands) 24 23% No specific method employed for this

descriptive study Not specified

(Finucane et

al., 2007)

Outpatients at Diabetes Dietetics Clinic

(Ireland) 432 59%

Telephone reminders 1 week before appointment. Up to 3 attempts were made

before patients were deemed uncontactable (274 patients were

contactable and 158 were uncontactable)

4 months

(Hickson et al., 2009)

Outpatients at intensive weight management

clinics (IWMC) (United Kingdom)

75

96% returned for second appointment

53% completed programme

Treatment group: A structured approach with six once-a-month appointments, a signed agreement to attend, an initial screening of readiness to change and

consistent advice from one dietitian. (Only patients who were motivated to lose weight

were enrolled). 6 months

Outpatients for weight loss at general dietetic

clinics (United Kingdom)

93

54% returned for second appointment

19% completed programme

Control Group: Patients were offered 5 appointments in the outpatient clinic

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1.3.3 Strategies to Improve Post-discharge Follow-up

Given the adverse consequences of malnutrition and likelihood of poor rates of

follow-up post-discharge, new strategies are needed to effectively manage these

patients. One possible model of care is a telephone and/or home visit follow-up

programme. Telephone-delivered interventions have emerged as an increasingly

popular means of delivering health promotion and behaviour change intervention

for patients with chronic disease (McBride & Rimer, 1999; Kay et al., 2006;

VanWormer et al., 2009). This individualised and convenient service could

improve patient compliance to follow-up. To date, there have been limited studies

published on the efficacy of telephone care and home visits to improve the

nutritional outcomes of malnourished patients discharged from hospital, with

existing research based on geriatric population (Feldblum et al., 2010), or the use

of this model of care in other settings i.e. preventing the deterioration of

nutritional status in oncology outpatients receiving radiotherapy (Isenring et al.,

2004).

The study by Feldblum looked at the effectiveness of post-discharge home visits

for 259 hospitalised adults aged 65 and older who were at nutritional risk as

determined by the SF-MNA (Feldblum et al., 2010). The intervention group

received individualised nutritional treatment from a dietitian in the hospital and

three home visits after discharge. The control group received one meeting with a

dietitian in the hospital or standard care. After 6 months, the mean change in

MNA score was significantly higher in the intervention group than in the control

groups after adjusting for education level and hospitalisation ward (3.01 ± 2.65

vs. 1.81 ± 2.97, p = 0.004). Mortality was significantly lower in the intervention

group than in the control group (3.8% vs. 11.6%, p= 0.046) (Feldblum et al.,

2010).

Another study provided telephone reviews as part of intensive nutrition support

between nutrition counselling sessions for oncology outpatients receiving

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radiotherapy to the gastrointestinal or head and neck area (Isenring et al., 2004).

In this randomised control trial, the intervention group received individualised

nutrition support in the form of regular and intensive nutrition counselling by a

dietitian. Nutrition counselling by the dietitian was provided within the first 4 days

of commencing radiotherapy and weekly for the course of radiotherapy

(approximately 6 weeks) and fortnightly for the remainder of the 12-week study

period. Telephone reviews were conducted between nutrition counselling

sessions. Individually tailored sample meal plans, recipe suggestions and

techniques to minimise the side effects of the tumour and therapy were provided.

Standard patient handouts were used, as well as high energy and snack ideas,

and protein exchange lists. If deemed appropriate, the dietitian would provide a

weekly supply of oral nutrition supplements for up to 3 months. The usual care

group received general nutrition advice provided by a nurse, no individualisation

of nutrition advice and less follow-up and referral to outpatient dietitians, which

was a maximum of two dietetic consultations. The intensive nutrition intervention

group had statistically smaller deteriorations in weight, nutritional status and

quality of life compared with those receiving usual care (Isenring et al., 2004).

Both the above studies are Level II studies (National Health and Medical

Research Council, 2009) which provided good evidence for the effectiveness of

either home visits or combination of outpatient visits and telephone follow-up up.

Such interventional studies with a control arm are not easy to carry out because

of ethical concerns, designing what the control group should receive and who

should be selected for which arm. In addition, home visits may not be possible for

many healthcare institutions and countries due to intensive resources needed

with regard to manpower, travelling expenses and time. If a ‘face to face’ visit

with a dietitian is crucial in contributing to the improvement of nutritional status for

malnourished patients, another strategy could be to assign home visits only for

patients who had defaulted outpatient follow-up and who had been triaged as not

progressing well nutritionally. This modality of follow-up has not been explored.

117


Summary of Issues in Post-discharge Follow-up of Malnourished Patients

There have been limited studies published on the follow-up rate and the effect of

combined telephone, outpatient and home visit follow-up on the nutritional

outcomes of malnourished patients discharged from the hospital. Specifically,

limiting home visits to patients who really need them has not been studied. A

study carried out in this area will provide evidence to the feasibility and

effectiveness of this strategy of follow-up for malnourished patients.

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1.4 OVERALL SUMMARY AND GAPS IN CURRENT RESEARCH

This literature review has revealed significant gaps in the current body of

knowledge, which can be presented as 4 broad topics.

Firstly, a critical step in managing malnutrition is to provide evidence that there is

indeed a problem. There have been scarce data on the prevalence and

outcomes of malnutrition in Singaporean hospitals. Specifically, there are no

published studies on the consequences of malnutrition that have adjusted for

disease complexities using DRG in adult hospitalised patients. Almost all studies

that compare the mortality rate of malnourished patients had not used the

national registry to track the mortality of patients post discharge. It is important to

determine the cost and clinical outcomes arising from malnutrition in hospitalised

patients and more so to use the national registry to track mortality and control the

outcomes for confounders which may likely affect the results.

Secondly, all patients admitted to hospital should be systematically screened,

using a nutrition screening tool that is simple, quick, reliable, valid and cost

effective. Although many nutrition screening tools exist, these have mostly been

validated in the Caucasian population. No nutrition screening tool has been

developed and validated for use in Singapore (or Asia) with its particular racial

mix. As Singapore consists of a unique multi-ethnic population, the applicability

of existing nutrition screening tools is uncertain, particularly the cutoffs used to

identify those at risk of malnutrition. The selection, reporting and interpretation,

including cutoffs, of nutrition screening may differ between different racial groups,

healthcare systems and cultural contexts (de Onis & Habicht, 1996; Chumlea,

2006). Hence development and validation of a malnutrition screening tool specific

to the Singaporean healthcare context is needed.

Thirdly, for a nutrition screening tool to be effective, it must be completed fully

and accurately. Studies have reported screening incompletion and error rates of

119


28-97% (Raja et al., 2008; Wong & Gandy, 2008; Neelemaat et al., 2011b;

Geiker et al., 2012). High levels of missing data (41- 47%) was found in

commonly used nutrition screening tools (Neelemaat et al., 2011b). Failure to

achieve accurate and complete nutrition screening will affect the final score

allocated to a patient, which may result in a malnourished or at risk patient not

being referred for nutritional intervention. To complete the process of nutrition

screening, any patient identified from screening to be malnourished or at risk of

malnutrition should be referred to receive a full nutrition assessment and

intervention (American Dietetic Association., 1994; Joint Commission

International, 2008). To date, there has not been any published study on the use

of quality improvement tools in addressing ways to improve the compliance rate

of nutrition screening and to improve the effectiveness of referral process for

patients identified as malnourished or at risk of malnutrition.

Fourthly, after a malnourished or at risk patient is identified and referred, nutrition

assessment has to be carried out to confirm and diagnose malnutrition, followed

by appropriate nutrition intervention by a dietitian. A review of the literature has

shown that SGA is a widely validated and accepted method to assess nutritional

status (Table 1.8), and that nutritional intervention has proven beneficial in

improving the outcomes of malnourished patients (section 1.3.1). However, to

comprehensively manage malnourished patients, ongoing monitoring and/or

intervention is required. From overseas studies, many patients are lost to follow-

up (Table 1.10) and we do not know as yet the rate of follow-up for malnourished

patients discharged from the hospitals in Singapore. In this area, there is also

limited evidence on effective methods of follow-up for post-discharge

malnourished patients.

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1.5 CONCEPTUAL FRAMEWORK OF RESEARCH PROGRAMME

Based on the literature review which has been presented in this chapter, a

conceptual framework is derived (Figure 1.6). The conceptual framework

includes the overarching research questions which will be addressed by this

research programme.

In the conceptual framework, it is proposed that a validated nutrition screening

tool should be used to screen all newly admitted patients. Individuals identified to

be at risk of malnutrition through nutrition screening should be referred in a timely

manner for a detailed nutrition assessment to diagnose the presence and

severity of malnutrition as a prerequisite for treatment. Thereafter, confirmed

cases should be provided with appropriate nutrition intervention in the hospital.

Due to the short length of hospital stay, these patients should be followed up

post-discharge to ensure positive nutrition and clinical outcomes. Telephone

consult can be employed to follow-up on the patients. From the tele-consult, if

nutritional problems still persist, patients should be encouraged to return for

follow-up with the dietitians at the outpatient clinic so that the dietitians are able

to reassess the patients and modify the treatment plan as necessary. If these

patients fail to turn up at the outpatient clinic, home visits by the dietitians can be

effected. Patients should be reassessed and have their nutrition care plan

modified if needed in the outpatient setting or in the community. The same

assessment tool used to diagnose malnutrition should be used to monitor the

patients; and evaluate the treatment and outcomes of the nutrition intervention.

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Figure 1.6: Conceptual Framework for the Identification and Management of Malnutrition in Hospitalised Patients

How do we best identify patients at

nutrition risk on admission to a

hospital in Singapore?

Is a validated & reliable nutrition screening tool

used? What is the

compliance to nutrition

screening?

Is referral process for

at risk patients

effective?

Is a validated nutrition

assessment tool used to diagnose

malnutrition?

Is nutrition support

effective?

What is the rate of dietetics

follow-up of malnourished patients post-discharge? Is there a better approach to follow up?

What is the effect

on outcomes?

Referral to

dietitian

Ongoing monitoring of intake by nurses

Monitoring Post-

discharge

Poor Intake

Negative screening

Well nourished

Malnourished

Positive screening (At risk)

Nutrition Screening

Nutrition Assessment

Nutritional Outcome

Clinical Outcome: - Mortality rate - Readmission rate - Length of hospital stay - Complications (pressure ulcers / Infections) Functional Outcome: - Quality of life - Handgrip strength Economic Outcome - Cost of hospitalisation

Re-assess and modify nutrition care if needed

Intervention/ Treatment

Follow-up

WHAT IS THE PREVALENCE OF MALNUTRITION IN A SINGAPORE HOSPITAL?

Signifies significant gaps in the current body of knowledge

122


From the conceptual framework, the following questions were raised:

1) What is the prevalence of malnutrition in a Singapore hospital?

2) How do we best identify patients at nutrition risk on admission to a hospital

in Singapore? Is a validated & reliable nutrition screening tool used? What

is the compliance to nutrition screening? Is the referral process for at risk

patients effective?

3) Is a validated nutrition assessment tool used to diagnose malnutrition?

4) Is nutrition support effective?

5) What is the rate of dietetics follow-up of malnourished patients post-

discharge? Is there a better approach to follow up?

6) What is the effect on outcomes?

Questions 1, 2 and 5 (circled) within the conceptual framework in Figure 1.6

represent significant gaps found in the current body of knowledge, which have

been covered in section 1.4. These led to five research questions which will be

presented in the next section.

123


1.6 RESEARCH QUESTIONS AND OBJECTIVES

The research questions address the significant gaps in current research, which

have been presented and discussed in sections 1.4 and 1.5. Each research

question is then addressed by a study with specific aims.

Research Question 1 (RQ 1): What is the prevalence of malnutrition in a Singapore hospital and its

prospective impact on clinical outcomes?

Objective 1

• To determine the prevalence of malnutrition on admission to a tertiary


stay, readmission and 3-year mortality.

Research Question 2 (RQ 2):

How do we best identify patients at nutrition risk on admission to a hospital in

Singapore?

Objective 2

• To develop and validate a new nutrition screening tool against Subjective

Global Assessment for use in the Singaporean adult population admitted

to an acute hospital.

124


Research Question 3 (RQ 3): Is the new nutrition screening tool valid and reliable when administered by the

intended users (nurses)?

Objective 3

• To confirm the reliability and validity of the new nutrition screening tool

administered by nurses against Subjective Global Assessment in a new

cohort of patients.


What is the compliance of nurses with nutrition screening and are patients

screened as ‘at risk’ referred to the dietitians? What measures can improve

compliance with nutrition screening and its referral rate?

Objective 4

• To investigate the compliance rate of nurses in conducting nutrition

screening and referring at risk patients to the dietitians; and determine

the effect of quality improvement initiatives in improving the overall

performance of nutrition screening.


What is the rate of dietetics follow-up of malnourished patients post-discharge?

Is there a better approach to follow up?

Objective 5

• To explore and determine the effectiveness of the current system and an

alternative model on dietetics follow-up rate of malnourished hospital


125


1.7 AIMS OF RESEARCH PROGRAMME

The proposed research programme will address significant gaps in the current

research and contribute to the Singaporean evidence-base. It will assist key

stakeholders to recognise the importance of managing malnutrition, and to

regard nutrition intervention as part of a holistic care plan for malnourished

patients or those at risk.

The aims of the research programme are to:

i) determine the prevalence of malnutrition on admission to a tertiary


stay, readmission and 3-year mortality,

ii) develop and validate a new nutrition screening tool for use in the

Singaporean adult population admitted to an acute hospital,

iii) confirm the reliability and validity of the new nutrition screening tool

administered by nurses in a new cohort of patients,

iv) investigate the compliance rate of nurses in conducting nutrition

screening and referring at risk patients to the dietitians; and determine

the effect of quality improvement initiatives in improving the overall

performance of nutrition screening and

v) explore and determine the effectiveness of the current system and an

alternative model on dietetics follow-up care for malnourished hospital


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Chapter 2: LINKING THE RESEARCH QUESTIONS

2.1 LINKING THE RESEARCH QUESTIONS AND OBJECTIVES

This thesis seeks to address major challenges and gaps in the healthcare

system to screen, manage and treat malnutrition in hospitalised patients. Is

malnutrition prevalent in newly hospitalised patients and what is the impact on

clinical outcome and cost? Is our screening system robust enough to identify

these patients? Following screening, is the referral process efficient enough to

channel these patients to the appropriate professionals? And finally is our

nutritional intervention effective beyond the hospital walls after the patient has

been discharged home?

Table 2.1 provides a brief overview of how the research questions and

objectives are addressed in the five research papers that make up this thesis.

The subsequent chapters will consist of separate research papers. All the

papers have either been published or accepted by peer reviewed indexed

journals.

2.2 HOW THE RESEARCH PROJECTS ARE RELATED The five research projects are closely related to one another, and will address

the research questions initially set out under the broader conceptual framework.

As the papers follow the usual format of scientific publications; namely

comprising sections for introduction, methodology, results, discussion and

conclusion, they are not discussed in detail within each chapter in order to

minimise repetition. However each chapter will include an introduction and

conclusion to link the research papers. Due to the difference in elapsed time

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needed for study implementation, data collection, data analysis, writing the

manuscripts and the turnaround time for successful publication, the papers were

not published in the chronological sequence of the research questions they

address. However for logical flow and ease of reading, the papers have been

arranged in their logical order. The format of each paper follows that of the

specific journal in which it was published, including referencing and English style

(British or American).

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Table 2.1: Research questions, objectives and relevant publications

RQ # Research Questions (RQ)

Objectives of Research Research Papers

RQ 1 What is the prevalence of malnutrition in a Singapore hospital? What is the prospective impact on clinical outcomes?

Objective 1 To determine the prevalence of malnutrition on admission to a tertiary hospital in Singapore and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality

Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality (Lim et al., 2012; Lim & Daniels, 2013)

RQ 2 How do we best identify patients at nutrition risk on admission to a hospital in Singapore?

Objective 2 To develop and validate a new nutrition screening tool against Subjective Global Assessment for use in the Singaporean adult population admitted to an acute hospital

Development and validation of 3-Minute Nutrition Screening (3-MinNS) Tool for acute hospital patients in Singapore (Lim et al., 2009)

RQ3 Is the new nutrition screening tool valid and reliable when administered by the intended users (nurses)?

Objective 3 To confirm the reliability and validity of the new nutrition screening tool administered by nurses against Subjective Global Assessment in a new cohort of patients

Validity and reliability of 3-Minute Nutrition Screening (3-MinNS) administered by nurses (Lim et al., 2013a)

RQ 4 What is the compliance of nurses with nutrition screening and are patients screened as ‘at risk’ referred to the dietitians? What measures can improve compliance with nutrition screening and its referral rate?

Objective 4 To investigate the compliance rate of nurses in conducting nutrition screening and referring at risk patients to the dietitians; and determine the effect of quality improvement initiatives in improving the overall performance of nutrition screening

Improving the performance of nutrition screening through continuous quality improvement initiatives (In press, 2014)

RQ 5 What is the rate of dietetics follow-up of malnourished patients post-discharge? Is there a better approach to follow up?

Objective 5 To explore and determine the effectiveness of the current system and an alternative model on dietetics follow-up rate of malnourished hospital patients post-discharge.

A pre-post evaluation of an ambulatory nutrition support service for malnourished patients post hospital discharge: a pilot study (Lim et al., 2013b)

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2.3 OVERVIEW OF RESEARCH METHODOLOGY

The study programme was conducted in four phases and summarised in Table

2.2.

i. a cross-sectional 3-year prospective study phase in which the data was

used to determine the prevalence and outcomes of malnutrition. This

phase also involved development and validation of a new nutrition

screening tool called 3-Minute Nutrition Screening (3-MinNS) (CHAPTER 3 AND CHAPTER 4)

ii. a cross-sectional prospective study to confirm the validity and determine

the reliability of 3-MinNS when used by nursing staff, the intended users of

the tool (CHAPTER 5) iii. a 6-year audit and quality improvement study to improve nurses’

compliance with 3-MinNS (CHAPTER 6) iv. a prospective interventional cohort study to evaluate the effectiveness of

an alternative ambulatory model of nutrition support for malnourished

patients discharged from the hospital (CHAPTER 7)

Table 2.2: Summary of study design, sample size and sampling strategy

Phase Study (Chapter) Design n Sampling

strategy

1

1 (Chapter 3) Prospective

818 Consecutive 2

(Chapter 4) Cross sectional

2 3 (Chapter 5) Cross sectional 121 Consecutive

3 4 (Chapter 6)

Prospective quality improvement study 4467 Consecutive

4 5 (Chapter 7)

Retrospective (Year 2008) Prospective pre-post study

(Year 2010)

261 163 Consecutive

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An overview of methodology for the research programme is presented in Figure

2.1, with each method explained in detailed within the published papers.

In phase one, nutrition assessment using Subjective Global Assessment (SGA)

was conducted on newly admitted patients aged 18 years and above, to

determine the prevalence of malnutrition in a Singapore acute hospital (n=818).

The clinical outcomes of these patients were prospectively tracked using a

Diagnosis-Related Groups (DRG) matched case control (well-nourished vs.

malnourished) design over 3 years and the results were adjusted for gender,

age and ethnicity. The same cohort of 818 patients was also screened using five

parameters that contribute to the risk of malnutrition. The parameters were

presence of unintentional weight loss in the past six months, intake in the past

one-week, body mass index, disease with nutrition risks and the presence of

muscle wasting in the temporalis and clavicular areas. The dietitian

administering SGA was blinded to the results of the nutrition screening

completed by a second dietitian. The sensitivity and specificity of individual

nutrition parameters as well as their different combinations were established

using the Receiver Operator Characteristics (ROC) curve. The best cutoff score

to identify malnourished patients or those at risk of malnutrition were determined

using SGA as a reference tool. The nutrition parameter (or its combination) with

the largest Area Under the ROC Curve (AUC) was chosen as the final screening

tool, which was named the 3-Minute Nutrition Screening (3-MinNS).

In phase two, three ward-based nurses administered the 3-MinNS to a new

group of patients within 24 hours of admission (n=121). A dietitian blinded to

these results conducted a nutrition assessment using SGA. To assess the

reliability of 3-MinNS, 37 patients screened by the first nurse were re-screened

by a second nurse within 24 hours, who was blinded to the results of the first

nurse. Receiver operator characteristic (ROC) curve analysis was performed to

determine the sensitivity and specificity of 3-MinNS when compared to SGA

(validity). The positive predictive value (PPV) and negative predictive value

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(NPV) for 3-MinNS were determined. Kappa score was used to determine the

inter-rater reliability of 3-MinNS between the nurses.

In phase three, annual audits were carried out from 2008-2013 to investigate the

incompletion and error rates of 3-MinNS (n = 4467). Quality improvement tools

such as Value Stream Mapping and the Plan-Do-Check-Act cycle were applied

in this phase. Root cause analysis was used to determine the best action plan.

Hospital-wide action plan implemented from 2009-2011 included 1) nutrition

screening training incorporated as part of nurses orientation programme, 2)

Nutrition Screening Protocol was made accessible to all staff via the staff

intranet, 3) nurse empowerment for online dietetics referral of at risk cases, 4)

closed-loop feedback system and 5) removing a component in the nutrition

screening that caused the most error without compromising sensitivity and

specificity, a decision supported by phase 2 study results.

In phase four, the effectiveness of the current system in following up

malnourished patients discharged from the hospital was audited retrospectively

on a consecutive sample of malnourished inpatients referred to dietetics

(n=261). The results were used to develop a novel model of care called

Ambulatory Nutrition Support (ANS) to follow-up these patients post-discharge.

Ambulatory Nutrition Support provided a combination of outpatient review,

telephone calls and home visits. The effectiveness of ANS was evaluated via a

prospective cohort study of adult inpatients referred to dietetics and assessed as

malnourished using Subjective Global Assessment (n=163). All subjects

received inpatient nutrition intervention and four months of ANS. Subjective

Global Assessment, body weight, quality of life using the Euro Quality of Life - 5

Domain Visual Analogue Scale (EQ-5D VAS) and handgrip strength were

measured at baseline and five months post-discharge. Paired t-test was used to

compare pre- and post-intervention results.

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Figure 2.1: Schematic diagram on the methodology of research programme Phase 1 (n=818) (CHAPTER 3 & 4) Phase 2 (n=121) (CHAPTER 5) Phase 3 (n=4467) (CHAPTER 6)

Recruitment Inclusion criteria: • 18-74 years old

• Not enrolled during previous admission • Not Paediatric, Psychiatry, ICU & Maternity cases

Nutrition Assessment (Dietitian II) Subjective Global Assessment (SGA) to determine

patients’ nutritional status within 48 hours of admission

Well-nourished

Prospective Outcomes Tracking • Length of hospital stay (LOS)

• Unplanned readmissions • Cost of hospitalization before government subsidy

• Mortality at 1, 2 & 3 years from index admission (Source: Hospital System & Singapore Death Registry)

Statistical Analyses • Mixed Model Analysis to analyze difference between well- nourished

and malnourished groups with DRG as random effect • Conditional Logistic Regression matching by DRG to evaluate the

association between nutritional status and outcomes (All results were controlled for gender, age and race and disease type and

complexity using DRG) (Participants who had been classified with a malnutrition sub-component in the DRG were reclassified with the corresponding DRG without malnutrition so that

matching between similar codes of DRG can be performed)

Malnourished

Nutrition Screening (Dietitian I) Testing of 5-items to determine

nutritional risk within 24 hours of admission

Not at risk At risk

Development of 3-Minute Nutrition Screening Tool Compares with reference standard (SGA)

Statistical Analyses The sensitivity and specificity were

established using the Receiver Operator Characteristics (ROC) curve and the best

cutoff scores determined. The nutrition parameter with the biggest Area Under the ROC Curve (AUC) was chosen as the final

3-Minute Nutrition Screening tool (3-MinNS).

Blinded

Recruitment Inclusion criteria:

• ≥ 21 years old • Oncology & Surgical wards

• Not enrolled during previous admission

SGA (1 Dietitian) Subjective Global Assessment (SGA) to determine

patients’ nutritional status within 48 hours of admission

3-MinNS (Nurse II & III) Within 24 hours of admission Blinded Blinded 3-MinNS (Nurse I)

Within 24 hours of admission

Statistical Analyses Kappa score to determine the inter-rater reliability of 3-MinNS among the nurses.

Statistical Analyses ROC curve analysis to determine the sensitivity and specificity of 3-MinNS when compared to SGA done. Spearman rho to

determine the correlation between 3-MinNS and SGA.

Annual Audits on Nutrition Screening (Hospital-wide) Inclusion criteria:

• All patients admitted to National University Hospital during audit periods • ≥ 21 years old, Not Paediatric cases

Year 2008 Baseline data

Year 2009 Baseline data

Year 2010 Post-

implementation data

Year 2012 & 2013 Post-

implementation data

Year 2011 Post-

implementation data

CQI CQI Sustenance

CQI = Continuous Quality Improvement Initiatives

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Phase 4 (n= 261 & 163) (CHAPTER 7)

Recruitment Inclusion criteria:

Patients referred to dietitian, assessed to be malnourished using SGA and have been provided with inpatient nutrition counselling and support,

Age ≥ 21 years Not on tube feeding or total parenteral nutrition,

Not Psychiatry, Maternity, Palliative Care patients Not patients discharged to nursing home or community hospital

Data collection • Measurements (same as at baseline) at 5 months post-

discharge • Measurement of follow-up rate post-discharge from hospital

2010 cohort (n = 163) 2008 cohort (n = 261)

Outpatient follow-up • Dietetic outpatient appointment arranged for

one-month post-discharge • Reminder sent by Short Messaging System

(SMS) or letter one-week prior to appointment

4-month Ambulatory Nutrition Support • Telephone calls at 1 week, 2 and 4 months post-discharge • Dietetic outpatient appointments at 1 and 3 months post-

discharge • Patients failing to attend either outpatient appointments were

telephoned, with home visit provided if required

Baseline measurements (≤4 days before discharge) • Weight and height • SGA • Mid arm anthropometry • EQ-5D Visual Analogue Scale (QOL) • Handgrip strength

Data collection • Measurement of follow-up rate post-

discharge from hospital

Statistical Analyses Paired t-test to compare baseline and post-intervention results.

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Chapter 3: PREVALENCE OF MALNUTRITION AND ITS IMPACT ON CLINICAL OUTCOMES AND COSTS

Publications:

1. Lim SL, Ong KCB, Chan YH, Loke WC, Ferguson M, Daniels L. Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality. Clinical Nutrition 2012. 31(3):345-350. (IF = 1.362)

2. Lim SL, Daniels L. Reply - Malnutrition and its impact on cost of

hospitalisation, length of stay, readmission and 3-year mortality. Clinical Nutrition 2013; 32(3):489-490. (IF = 1.362)

3.1 Introduction There is a lack of evidence on the prevalence and prospective outcomes of

malnutrition in Singaporean hospitals. What is the evidence of there being a

problem of malnutrition in the hospital? What is the magnitude of the problem?

Providing evidence on the prevalence and outcomes of malnutrition in

hospitalised patients in Singapore is the first step in defining the problem.

Hence, this study was undertaken to establish the prevalence of malnutrition

and its impact on clinical outcomes and cost in hospitalised patients in

Singapore.

It is commonly believed that any association of malnutrition with poor outcomes

is due to underlying chronic diseases (Elia, 2006). Although many overseas

studies have been done on clinical outcomes of malnutrition, none have used

Diagnosis-Related Groups (DRG) to control for disease and its complexities.

The extent of malnutrition and its independent effect on outcomes must be

determined and understood prior to requesting for resources, planning and

developing any intervention.

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The paper in this chapter underscores the prevalence of malnutrition in a tertiary

hospital in Singapore and its impact cost of hospitalisation, length of stay,

readmission and 3-year mortality, controlling for DRG.

3.2 Publication

Refer to paper or go to: 1) http://eprints.qut.edu.au/50643/

2) http://eprints.qut.edu.au/59962/

3.3 Conclusion

Malnutrition was evident in up to one third of inpatients in an acute hospital in

Singapore. After controlling for the potential confounders of age, gender,

ethnicity and diagnosis- related groups, malnourished patients stayed in the

hospital 1.5 times longer than well-nourished patients (p = 0.001) and were

almost twice as likely as well-nourished patients to be readmitted within 15 days

of discharge (p=0.025). They incurred 24% more cost than well-nourished

patients. Even after controlling for the confounders mentioned above,

malnutrition posed almost four-fold and three-fold increases in the risk of death

at 1-year and 3-year post-discharge, respectively (HR = 4.4, CI 3.3-6.0,

p<0.001). As such, this paper provides strong support that malnutrition is a

condition that must be addressed, and there is an urgent need for strategies to

prevent and treat malnutrition in hospitalised patients.

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http://eprints.qut.edu.au/50643/�


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Chapter 4: DEVELOPMENT AND VALIDATION OF 3-MINUTE NUTRITION SCREENING (3-MinNS)

Publication:

Lim SL, Tong CY, Ang E, Lee EJ, Loke WC, Chen Y, Ferguson M, Daniels L. Development and validation of 3-Minute Nutrition Screening (3-MinNS) Tool for acute hospital patients in Singapore. Asia Pacific Journal of Clinical Nutrition. 2009;18(3):395-403. (IF = 1.438)

4.1 Introduction

From Chapter 3, we know that malnutrition is prevalent in a Singapore hospital

and leads to adverse outcomes, independent of illness and its complexity. About

one third of hospitalised patients are already malnourished upon admission.

Therefore, it is important to screen newly admitted patients so that those

identified to be at ‘nutritional risk’ are systematically referred for timely nutrition

assessment and intervention.

In order to prevent and treat malnutrition, we must first know who is at risk.

Although there are a number of screening tools available, limitations exist for

each, as discussed in Chapter 1 and presented in Table 1.4. Most tools were

developed overseas and validated in the Caucasian population and their

suitability for use in the Singaporean multi-ethnic, large tertiary hospital has not

been established. The selection, reporting and interpretation, including cutoffs,

of nutrition screening may differ between different racial groups, healthcare

systems and cultural contexts (de Onis & Habicht, 1996; Chumlea, 2006). The

complexity and time-intensive nature of many nutrition screening tools such as

in NRIb (Wolinsky et al., 1985), Nursing Nutritional Assessment Tool (Scanlan et

al., 1994) and Screening Nutritional Profile (Hunt et al., 1985a) render them

impractical in Singapore, where patient to nurse ratio was high (7 patients to 1

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nurse in the year 2002 and before). In addition to this, feedback sessions with

nursing staff identified ambiguity in their understanding of how to score a patient

when administering nutrition screening such as the Derby Nutritional Score

(Goudge et al., 1998). For example, what does loss of appetite mean? How

much of a decrease in food intake is considered significant? The MUST

(Stratton et al., 2004), SNAQ (Kruizenga et al., 2005a) and NRS 2002 (Kondrup

et al., 2003b) had not been published when the candidate developed the NUH

Nutrition Screening Tool in 2002. Although the Malnutrition Screening Tool

(MST) (Ferguson et al., 1999a) perhaps may have been a suitable tool for

Singapore, this was not readily accessible at that time. In addition, many

screening tools such as Derby Nutritional Score, MUST, NRS 2002, MNA-SF

and Nutrition Risk Score (Reilly et al., 1995), which require patient’s weight,

height and body mass index may not be completed in a sizeable proportion of

patients (Wong & Gandy, 2008; Porter et al., 2009). No nutritional screening tool

had yet been properly validated for hospitalised adults in Singapore. Hence,

development and validation of an effective nutrition screening tool specific to the

Singaporean healthcare context was mooted. The original screening tool was

created in 2002, and was subsequently revised as a result of a validation study

within this research programme, which is presented in this chapter.

The paper in this chapter addresses the research question “How do we best

identify patients at nutrition risk on admission to a tertiary hospital in

Singapore?” The aim of the study was to develop and validate a new nutrition

screening tool against Subjective Global Assessment for use in the Singaporean

adult population admitted to an acute hospital.

4.2 Publication

Refer to paper or go to: http://eprints.qut.edu.au/29117/

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4.3 Conclusion

With the validation of 3-MinNS carried out on consecutive patients via an

independent, blinded comparison with SGA, which is a valid reference standard,

this study has provided the first Level II evidence under NHMRC (National

Health and Medical Research Council, 2009) criteria for nutrition screening in

hospitalised patients in Singapore. The 3-Minute Nutrition Screening tool was

both sensitive (86%) and specific (83%) in detecting nutritional risk in newly

admitted patients, with three as the best cutoff score. It has the added

advantage of summative scoring and cutoff points useful to define a protocol for

subsequent action. As the 3-MinNS is a simple and efficient tool to administer to

acute hospital patients in Singapore, it will assist healthcare workers to carry out

nutrition screening accurately and promptly so that patients who require nutrition

intervention can be managed appropriately.

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Chapter 5: VALIDITY AND RELIABILITY OF 3-MINUTE NUTRITION SCREENING

ADMINISTERED BY NURSES

Publication:

Lim SL, Ang E, Foo YL, Ng LY, Tong CY, Ferguson M, Daniels L. Validity and reliability of nutrition screening administered by nurses. Nutrition in Clinical Practice. 2013; 28:730-736. (IF = 1.594)

5.1 Introduction The paper in Chapter 4 focused on determining the validity and reliability of 3-

Minute Nutrition Screening (3-MinNS), using one dietitian to administer nutrition

screening and another to conduct SGA as the reference standard (Lim et al.,

2009). Not only must the tool be valid but validation itself should ideally be

performed using the intended assessors. A survey carried out in the US,

showed that 84% of nutrition screening was administered by nursing staff

(Chima et al., 2008). Although in practice nutrition screening is commonly

undertaken by nursing staff, few studies have used nurses to validate nutrition

screening tools. Most studies have used researchers, dietitians or dietetic staff

to implement nutrition screening (Ferguson et al., 1999a; Kyle et al., 2006; Kim

et al., 2011; Velasco et al., 2011). As nutrition screening is usually administered

by nurses, it is critical that the reliability and validity of 3-MinNS be established

in this user group. Knowing that the 3-MinNS tool would eventually be used by

nurses to screen all newly admitted patients in NUH, it was only practical to let

the intended assessors (which would be the nurses) perform the screening tool

in this study. Hence, the paper in this chapter seeks to test the validity of 3-

MinNS when used by nurses on a new sample of patients. This paper also

provides new information on the reliability of the tool among nurses that was not

addressed in the earlier paper.

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The paper in this chapter addresses the research question “Is 3-MinNS valid

and reliable when used by the intended users (nurses)?” The aim of the study

was to confirm the reliability and validity of the new nutrition screening tool

administered by nurses against SGA in a new cohort of patients.

5.2 Publication


5.3 Conclusion

The results of this study confirm the validity of 3-MinNS when used by nurses.

The sensitivity and specificity of 3-MinNS were even better than the earlier study

(89% and 88% respectively) when administered by the nurses. There was also

good agreement between nurses administering the tool (reliability = 78.3%, k =

0.58, p<0.001). In summary, the last two chapters (Chapters 4 and 5) have

provided an evidence-base that the 3-MinNS is a sensitive, specific and reliable

tool that can be administered by dietitians and nurses on newly admitted

hospitalised patients to identify patients at risk of malnutrition.

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502812 NCPXXX10.1177/0884533613502812Nutrition in Clinical PracticeLim et alresearch-article2013

158

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Chapter 6: IMPROVING THE PERFORMANCE OF NUTRITION SCREENING

Publication:

Lim SL, Ng SC, Lye J, Loke WC, Ferguson M, Daniels L. Improving the performance of nutrition screening through continuous quality improvement initiatives. The Joint Commission Journal on Quality and Patient Safety 2014. (In press)

6.1 Introduction The previous two chapters established that the 3-MinNS is a valid and reliable

nutrition screening tool for newly hospitalised patients in Singapore. However for

a nutrition screening tool to be effective, beyond being validated and reliable, it

must be completed fully and accurately. It will not serve its purpose well if not

done correctly or if patients identified as being at nutritional risk are not given

intervention. Addressing compliance with nutrition screening and ensuring that

malnourished patients are referred in a timely manner are critical steps to

ensure these patients receive early nutrition intervention. It is important to

conduct process evaluation of implemented nutrition screening tools as part of

quality assurance. The literature reveals high levels of screening incompletion

and error rates as discussed in section 1.2.5 and summarised in Table 1.9.

Incompletion and error rates range from 30-97% for a range of commonly-used

screening tools. No published studies have described the use of quality

improvement tools to facilitate improvements in the compliance to nutrition

screening and its referral process. Hence, this topic is ripe for research. The

paper in this chapter evaluates quality improvement initiatives to improve the

rate of compliance and referral, which is a considerable challenge for a large

tertiary hospital employing over 3200 nursing staff.

The paper seeks to address these research questions: “What is the compliance

of nurses with nutrition screening and are patients screened as ‘at risk’ referred

to the dietitians? What effective measures can improve compliance with nutrition

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screening and its referral rate?” It aims to investigate the compliance rate of

nurses in conducting nutrition screening and referring at risk patients to the

dietitians; and determine the effect of quality improvement initiatives in

improving the overall performance of nutrition screening.

6.2 Publication

Refer to paper or go to QUT ePrints (paper available from April 14 onwards)

6.3 Conclusion This chapter shows that quality improvement initiatives were effective in

reducing the incompletion and error rates of nutrition screening, and led to

sustainable improvements in the referral process of patients at nutritional risk.

After the implementation of the quality improvement action plan, error rates were

reduced to from 33% in 2008 to 7% and 5% in 2012 and 2013 respectively.

From the audit database and root cause analysis, we were able to understand

the areas which caused the most errors. We were then able to devise action

plans, which when implemented, reduced the error rates substantially. Blank or

missing nutrition screening forms came down from 8% to 1%, with sustained

results for four consecutive years. Patients scored as being at risk of

malnutrition but were not referred to a dietitian was reduced from 10% in 2008 to

3% in 2012 and 2013. Direct online referral by the nurses to the dietitians was

the most effective initiative in improving the referral rates of patients at risk of

malnutrition.

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Chapter 7: FOLLOW-UP FOR MALNOURISHED POST-DISCHARGED HOSPITAL PATIENTS

Publication:

Lim SL, Lin XH, Chan YH, Ferguson M, Daniels L. A pre-post evaluation of an ambulatory nutrition support service for malnourished patients post hospital discharge: a pilot study. Annals Academy of Medicine Singapore. 2013; 42:507-513. (IF = 1.362)

7.1 Introduction

The first study in this research programme has indicated that malnutrition is

prevalent in newly hospitalised patients and leads to adverse outcomes

(Chapter 3). A robust screening process has been put in place to identify these

patients so that they receive nutritional intervention (Chapters 3, 4 and 5).

However in Singapore and many other countries, the short length of hospital

stay (averaging 4 days) (OECD., 2011) limits the scope of inpatient nutrition

intervention for malnourished patients, with improvements in nutritional status

unlikely to be seen in this short time frame despite receive nutritional

intervention and follow up from dietitians in the wards. These patients potentially

return to the community malnourished, and are often readmitted, causing a

vicious cycle. Therefore, it is imperative that we follow-up these patients after

they are discharged for ongoing monitoring and treatment. Discharged patients

are often given follow-up appointments to return to the clinic to see the dietitian.

But the current literature showed that the issue of patients becoming lost to

follow-up is common, with a dropout rate ranging from 54-58% of total dietetic

outpatient attendances (refer to section 1.3.2 and Table 1.10). Only one small

study carried out in Netherlands on 24 patients focused on follow-up rates of

malnourished patients. The study reported that 77% of malnourished patients

seen in the wards were lost to Dietetics follow-up after discharge (van Bokhorst-

de van der Schueren et al., 2005). There is obviously a gap in practice and a

gap in the current literature.

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Prospective studies are also lacking that show improvement in nutritional

outcomes if appropriate nutrition support and follow-up are provided for

malnourished discharged patients. Hence, the research questions in this chapter

are “What is the rate of dietetics follow-up of malnourished patients post-

discharge? Is there a better approach to follow up?” The paper aims to explore

and determine the effectiveness of the current system and an alternative model

on dietetics follow-up rate of malnourished hospital patients post-discharge.

7.2 Publication


7.3 Conclusion

This pilot research provides initial evidence that an Ambulatory Nutrition Support

(ANS) service consisting of clinic appointments, telephone calls and home visits

provides an effective model of follow-up for malnourished hospital patients post-

discharge, and is able to improve nutritional outcomes in this patient group. The

ANS service achieved 100% follow-up of malnourished inpatients within four

months of discharge from the hospital; a substantial improvement compared to

the 15% follow-up rate pre-ANS. More importantly, the nutritional indicators,

quality of life and functional status improved significantly in patients who

underwent ANS. Mean weight improved from 44.0 ± 8.5kg to 46.3 ± 9.6kg, EQ-

5D VAS from 61.2 ± 19.8 to 71.6 ± 17.4 and handgrip strength from 15.1 ± 7.1

kg force to 17.5 ± 8.5 kg force (p<0.001 for all). Seventy-four percent of patients

had an improvement in their SGA score and 67% improved in their quality of life.

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Chapter 8: DISCUSSION AND RECOMMENDATIONS

8.1 OVERVIEW OF RESEARCH QUESTIONS AND KEY FINDINGS

This chapter presents an overview of the results of the studies, highlights the

significance of the research, its contributions to scientific knowledge as well as

its impact to practice. The strengths and limitations of the research will also be

presented, followed by recommendations.

The over-arching research questions were:

1. What is the prevalence of malnutrition in a Singapore hospital and its

prospective impact on clinical outcomes and cost?

2. How do we best identify patients at nutrition risk on admission to a

hospital in Singapore?

3. Is the new 3-MinNS tool valid and reliable when used by the intended

users (nurses)?

4. What is the compliance of nurses with nutrition screening and are

patients screened as ‘at risk’ referred to the dietitians? What measures

can improve compliance with nutrition screening and its referral rate?

5. What is the rate of dietetics follow-up of malnourished patients post-

discharge? Is there a better approach to follow-up malnourished hospital

patients post-discharge?

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8.1.1 Prevalence of malnutrition and outcomes The prevalence of malnutrition in a Singapore tertiary teaching hospital was one

third of newly hospitalised adult patients. In this study on 818 patients newly

admitted to the hospital, the highest prevalence of malnutrition was found in

patients from oncology (71%), endocrinology (48%) and respiratory medicine

(47%). Malnourished patients tended to be older (58 years vs. 49 years, p <

0.001, 95% CI 7-11) and were more likely to be male (32% vs. 26%, p=0.016).

There was no statistical difference in the prevalence of malnutrition among

different races in Singapore. After controlling for the potential confounders of

gender, age, race and disease complexities using DRG, analysis of the data

found that malnourished patients stayed in the hospital longer and were more

likely to be readmitted within 15 days of discharge. Malnutrition was a significant

predictor of overall mortality, and the effect was pronounced even at three years

post-discharge. The average cost of hospitalisation was higher for malnourished

patients.

Although previous studies have shown a prospective association between

malnutrition and clinical outcomes, the confounding effect of disease and its

complexity has seldom been taken into consideration (Chima et al., 1997;

Middleton et al., 2001). While it is widely agreed that disease and malnutrition

are closely linked (Jeejeebhoy, 2000; Pirlich et al., 2003), it has been argued

that LOS, mortality and hospitalisation costs are primarily determined by the

patient’s medical condition, and any association with malnutrition is due to

confounding (Elia, 2006). In this study, the matched case control design based

on DRG showed that malnutrition was an independent predictor of length of

hospital stay, readmission, hospitalisation cost and mortality.

To date, this is the only study which has tracked the mortality of hospitalised

patients for 3 years post-discharge using national death registry data and

matching for DRG. Malnourished patients had four times and three times higher

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risk of death at one year and three year post-discharge, respectively (adjusted

hazard ratio = 4.4, 95% CI 3.3-6.0, p < 0.001). A similar study using national

registry data found a comparable mortality in malnourished patients at 1 year

(30% versus 34% in this study), but did not control for confounders (Middleton et

al., 2001). Other studies that associated malnutrition with long-term mortality

have been conducted mainly on elderly participants and did not use the national

death registry to track mortality (Sullivan & Walls, 1998; Miller et al., 2002;

Cereda et al., 2008b).

The current study found that malnourished patients stayed in the hospital one

and half times longer than well-nourished patients (6.9 ± 7.3 days vs. 4.6 ± 5.6

days, p < 0.001), which is consistent with other studies reporting longer LOS in

malnourished patients (Middleton et al., 2001; Correia & Waitzberg, 2003).

Malnourished patients cost an average of three times more than well-nourished

patients. This effect of malnutrition on hospitalisation cost was statistically

significant when matched for DRG, although this was not sustained when the

results were further adjusted for ethnicity, age and gender. These findings echo

previous studies which have linked malnutrition with higher hospitalisation costs

(Chima et al., 1997). These increased costs are indirectly attributed to longer

hospital stay (Correia & Waitzberg, 2003; Planas et al., 2004), increased use of

hospital resources (Correia & Waitzberg, 2003), higher rate of re-admission

(Planas et al., 2004), increased rates of infection (Rypkema et al., 2004) and

poor wound healing (Banks et al., 2010b).

Malnourished patients were found to have double the risk of readmission within

15 days in comparison to well-nourished patients (RR = 1.9, p < 0.001, 95% CI

= 1.1-3.2). However at 90 days and six months, even though there was

statistical significance when readmissions were controlled for age, gender and

ethnicity, the effect disappeared after matching for DRG. Planas et al (2004)

showed that malnourished patients were one and a half times more likely to be

readmitted within 6 months of discharge from the hospital but the results were

not controlled for any confounders (Planas et al., 2004).

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Only a very small fraction of patients identified as malnourished in this study had

been classified under the DRG co-morbidity as malnourished (3 out of 235

patients). It is evident that the majority of malnourished patients in National

University Hospital were either not recognised, or not accurately documented

and coded for DRG. This scenario was also observed in Australia and Spain

whereby less than 2% of inpatients were coded as malnourished (Marco et al.,

2011; Rowell & Jackson, 2011), in contrast to many studies reporting the

prevalence of malnutrition in hospitals to be more than 30% (Norman et al.,

2008b). Accurate diagnosis and coding for malnutrition could result in a DRG

with a higher weighting, which would more accurately reflect the resource

requirement for these patients. In some countries this would increase the

amount of financial reimbursement received by the hospital (Delhey et al., 1989;

Funk & Ayton, 1995; Amaral et al., 2007). More importantly, the accurate

diagnosis of malnutrition is crucial so that nutrition support can be extended to

these patients to help improve patient outcome.

Impact on Practice

This study has provided the first published evidence that malnutrition is

prevalent in a Singapore hospital and independently leads to poor outcomes

regardless of the underlying disease and its complexities.

Strengths

The study utilised a large sequentially recruited sample representative of

patients admitted to a major Singaporean tertiary hospital. Prospective tracking

of hospitalisation outcomes and 3-year mortality based on national death

registry record are further strengths of this study. No prior studies have

controlled for the confounding effect of disease and its complexities on

malnutrition outcomes and only one study has used national death register data

to determine the 1-year mortality outcomes of patients (Middleton et al., 2001).

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Limitations

This study was not able to monitor patients readmitted to other hospitals, and

thus readmission rates might be underestimated. However the likelihood of

readmission to other hospitals is low in our local experience, as most patients

prefer to return to the hospital closest to their homes, where their medical

records are held and where they attend post-discharge outpatient clinics. It

addition, it is the national policy in Singapore for public ambulance to take

emergency patients to the hospital nearest to their home.

Another limitation of this study is a lack of data on the number of study patients

referred for treatment of malnutrition or the outcome of that treatment. At the

time of this study (2006), access to inpatient dietetic services for assessment

and treatment of malnutrition was solely through medical referral by hospital

policy, and therefore it is likely that a substantial proportion of malnourished

patients were untreated (Bavelaar et al., 2008; Lamb et al., 2009). It is possible

that in a proportion of patients, nutritional status improved during or subsequent

to their admission. However, this proportion would likely be small and would

tend to attenuate associations between nutritional status at admission and

clinical outcomes.

8.1.2 Identifying patients at nutrition risk

This section discusses the two studies on the validation of 3-MinNS.

This first study developed and validated a new nutrition screening tool (3-

MinNS) for hospitalised adult patients in Singapore. Statistical analysis using the

ROC curve found that the most desirable among the five parameters tested in

terms of sensitivity and specificity was the combination of weight loss, nutritional

intake and muscle wastage. It was found that 3-MinNS was both sensitive (86%)

and specific (83%) in the determination of nutritional risk in newly admitted

patients. The 3-MinNS had good correlation with SGA, with the added

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advantage of summative scoring and cutoff points useful to define a protocol for

subsequent action. It was able to differentiate patients at risk of moderate

malnutrition and severe malnutrition for prioritization and management

purposes. 3-Minute Nutrition Screening is non-invasive and does not require

expensive equipment or blood tests as is the case for a number of commonly

used nutrition screening tools such as the Nutrition Risk Index (NRI), Prognostic

Nutritional Index (PNI) and Maastrich Nutrition Index (MNI) (Schneider &

Hebuterne, 2000; Corish et al., 2004). Subsequent to the publication of 3-

MinNS, a validation study on NRS-2002 and MUST was published which

showed good sensitivity and specificity when compared to SGA (NRS-2002:

74% sensitive, 87% specific, MUST: 72% sensitive, 90% specific) (Velasco et

al., 2011). However the assessors were not blinded to the screening and

assessment results. Hence, observer bias might have occurred.

The second study confirms the validity of 3-MinNS when implemented by

nurses, the intended users of the tool, on a new cohort of hospitalised patients.

The sensitivity (89%) and specificity (88%) of 3-MinNS in this study were slightly

better than that of the earlier validation study, where 3-MinNS was implemented

by dietitians blinded to the screening results of another dietitian. The correlation

between 3-MinNS administered by nursing staff and SGA implemented by the

dietitian was good (r=0.78, p<0.001). Although in practice nutrition screening is

commonly undertaken by nursing staff, few studies have used nurses to validate

nutrition screening tools. Most studies have used researchers, dietitians or

dietetic staff to implement nutrition screening (Ferguson et al., 1999a; Kyle et

al., 2006; Kim et al., 2011; Velasco et al., 2011). Recent validation studies

using nursing staff to administer screening and a dietitian to complete nutrition

assessment in a blinded manner were conducted with the British Nutrition

Screening Tool (NST) (Mirmiran et al., 2011), MST and MUST (Lawson et al.,

2012). These studies showed that when the sensitivity was good, the specificity

was compromised and vice-versa (NST: 62% sensitive, 87% specific; MST: 45%

sensitive, 86% specific; MUST: 54% sensitive, 78% specific). The 3-MinNS

however was able to achieve good sensitivity and specificity at the same time

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(89% and 88%) despite using nurses to conduct the screening and blinding to

the nutrition assessment results of the dietitian (Lim et al., 2013a).

In addition, this second study provided new data on the reliability of 3-MinNS,

which was not addressed in the first study. It shows good inter-rater reliability of

3-MinNS between nurse (agreement = 78.3%, k = 0.58, p<0.001)s. Several

inter-rater reliability tests have been performed on nutrition screening tools,

however many of these compared the results of dietitian with dietitian, or

dietitian with nursing staff (Reilly et al., 1995; Ferguson et al., 1999a; Burden et

al., 2001). These studies generally show good agreement, although MST and

Nutrition Risk Screening (NRS) have fared better than Nursing Nutritional

Assessment (NNA) (Reilly et al., 1995; Ferguson et al., 1999a; Isenring et al.,

2006). Only two studies examining inter-rater reliability between nurses have

been identified (McCall & Cotton, 2001; Mirmiran et al., 2011). In the Mirmiran et

al. (2011) study, a good level of agreement was found between nursing staff

administering the British Nutrition Screening Tool (NST) (Kappa = 0.71)

(Mirmiran et al., 2011). In contrast, McCall and Cotton (2001) found consistent

disagreement between nursing staff administering NNA, which they attributed to

subjective interpretation of questions within the tool (McCall & Cotton, 2001). In

this current study, each nurse was well trained in administering 3-MinNS, and

used the tool frequently in their daily practice. The scoring method and

objectivity of the questions within the 3-MinNS tool provided standardised

response options for the nurses. As 3-MinNS included assessment of muscles

at the temporalis and clavicular areas, nurses were trained using pictures of

different scorings of muscle wastage at these areas.

As 3-MinNS is simple and rapid to administer to acute hospital patients, and

enables healthcare workers to carry out nutrition screening accurately and

promptly, it is currently considered the best available nutrition screening tool to

identify patients at nutrition risk on admission to a hospital in Singapore.

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Impact on Practice

More than 7000 nurses and dietitians have been trained on 3-MinNS in

Singapore and Malaysia. Through multiple platforms such as publications and

presentations at local and international conferences, 3-MinNS has been adopted

and implemented in the following organisations:

Singapore

• National University Hospital

• Mount Alvernia Hospital

• Farrer Park Hospital

• United Medicare Nursing Home

• Man Fut Thong Nursing Home

• Sree Narayanan Nursing Home

• Khoo Teck Phuat Hospital

• Alexandra Hospital

• Gleneagles Hospital

• Raffles Hospital

Malaysia

• University Hospital Kuala Lumpur

Strengths

The 3-Minute Nutrition Screening tool was the first nutrition screening tool

developed in an Asian context; and specifically for Singapore with its particular

racial mix. The scoring system based on severity of nutritional indicators within

3-MinNS minimises ambiguity and the cutoff score for action guides the

healthcare professionals in their next course of action, i.e. whether to refer the

patient to the dietitian. The study was also the first validation study of a nutrition

screening tool in Singapore and Asia, which provides data on the sensitivity,

specificity, PPV and NPV of the tool. Further merits of this study are the large

sample size (n=818) consisting of a broad range of patients, recruitment of

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subjects from a randomly determined sequential sample, and the blinded

reference method assessor. Prior to our study, most validation studies on

nutrition screening tools have not been conducted with blinding of the

assessors.

Both the validation studies on 3-MinNS used SGA as a reference standard.

Subjective Global Assessment is a well validated nutrition assessment tool and

prognostic indicator (Barbosa-Silva & Barros, 2006). For this reason, it is widely

used as a reference method for validating screening and assessment tools (Kyle

et al., 2006; Kim et al., 2011).

Limitations

In the first validation study, the study sample was representative of the hospital’s

admission profile for gender and race but not for age. Although the study sample

was slightly older than the hospital population, this difference is unlikely to be

clinically significant or impact on results. The study protocol required that the

nutrition screening be completed within 24 hours and the reference standard

SGA within 48 hours, which may result in respondent bias as a patient may

respond differently or unable to answer based on their level of alertness and

medical condition at the time of nutrition screening and assessment. However,

the effect of this potential limitation was expected to be minimal as SGA was

completed within 24 hours for 90% of the study participants and changes in

nutritional status rarely occur over this short period of time.

In the second validation study, the study sample may not be representative of

the general hospital population as the participants were recruited from the

oncology and surgical wards. Oncology and surgical wards were chosen in

order to obtain a sufficient number of malnourished patients needed to

determine the sensitivity of the tool and both these specialties, especially

oncology, are known to have high prevalence of malnutrition. This is

advantageous as the nurses in these wards were used to working with

malnourished patients and nutrition may have higher profile on these wards than

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in the general wards. In addition, the first study on the validation of 3-MinNS and

as presented in Chapter 5 had addressed the multidisciplinary setting (Lim et al.,

2009).

8.1.3 Compliance and referral process of nutrition screening Even with the use of a valid and reliable nutrition screening tool, inaccurate

screening results may occur if the tool has missing data or is completed

erroneously. Studies have reported screening incompletion and error rates of

28-97% (Wong & Gandy, 2008; Neelemaat et al., 2011b). This may result in the

under-recognition and subsequent under-treatment of a malnourished or at-risk

patient. This problem is exacerbated if appropriate patients are not referred to a

nutrition-trained professional. A study by Kondrup et al (2002) showed that 53%

of patients identified as at nutritional risk did not have a nutrition plan

implemented (Kondrup et al., 2002).

In NUH, nutrition screening error rates were 33% and 31% in 2008 and 2009

respectively, with 5% and 8% blank or missing forms. From the study, we found

that despite the completion of nutrition screening within 24 hours of admission,

the entire process from nutrition screening to intervention by a dietitian took up

to 8.6 days, of which 7.5 days comprised of multiple activities (value added and

non-value added) preceding a dietetics referral. The mean time lag between

screening and referral was 4.3 ± 1.8 days. Further drilling down of the process

identified the reasons for the long turnaround to be: (1) only doctors were

allowed to make dietetics referral for patients at nutritional risk, which resulted in

(2) the nurses having to constantly remind the doctors to make a dietetics

referral, which consumed a considerable amount of time.

Following root cause analysis, a list of quality improvement activities was

implemented. They included 1) establishing a nutrition screening protocol in the

hospital system, 2) nutrition screening training incorporated as part of the

compulsory nurses orientation programme, 3) nurse empowerment for online

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dietetics referral of at risk cases, 4) closed-loop feedback system and 5)

removing a component of the nutrition screening that caused the most error

without compromising sensitivity and specificity. After the implementation of the

quality improvement action plan, nutrition screening error rates were

significantly reduced from 33% to 5% and blank or missing forms from 8% to

1%. The referral rate for patients at risk of malnutrition also improved from 10%

drop-referral to 3%. With the direct online referral system from the nurses, there

was a 92% reduction in turnaround time from nutrition screening to referral from

4.3 ± 1.8 days to 0.3 ± 0.4 days (p < 0.001). This study provided further

evidence on the capacity of the 3-MinNS to be completed accurately by nurses

so that newly admitted patients at nutritional risk can be provided with the

appropriate intervention as soon as possible.

Impact on Practice

This quality improvement study has significantly changed practice in a large

tertiary hospital which employs more than 3000 inpatient nurses, and has

resulted in excellent compliance to nutrition screening and referral of ‘at risk’

patients to the dietitians. The practical and effective action plan implemented

provides a positive case study for other organisations who are seeking ways to

improve on their nutrition screening and compliance rates.

Strengths

This study has several strengths, first of which is the large sample size of the

audits and consecutive sampling method. It is also amongst the first to report

the effectiveness of various quality improvement initiatives in increasing

compliance with nutrition screening, including the referral of care for appropriate

patients. The 93% compliance rate and 99% completion rate achieved in this

study are excellent when compared to other similar studies. Previous nutrition

screening audit studies have used only training as an intervention to improve the

compliance rate with limited success (Raja et al., 2008; Wong & Gandy, 2008).

The current study describes evidenced-based quality improvement measures

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which were implemented successfully hospital-wide to improve the management

of malnourished or at risk patients.

Limitations

Given that this study is a quality improvement project, it did not include a control

group. Hence it could not be determined if the action plan was solely

responsible for the improvement in the compliance and referral rates. In

addition, the more efficient referral process has inevitably increased the

workload of dietetics, although the clinical and cost benefit to patients outweighs

the cost arising from additional resources required.

8.1.4 Follow-up of malnourished patients post discharge

In 2008, only 15% of malnourished patients discharged from NUH returned for

outpatient dietetic follow-up within four months of discharge from index

admission, and only 2% attended more than one dietetics outpatient clinic

appointment. This poor rate of follow-up is consistent with data from other

studies, which have shown that 54 to 58% of patients fail to attend scheduled

outpatient appointments (Gallagher, 1984; Finucane et al., 2007). In one study,

of the 54% of malnourished patients seen by a dietitian during admission only

23% were followed up after discharge (van Bokhorst-de van der Schueren et al.,

2005).

In response to the 2008 data, an Ambulatory Nutrition Support (ANS) service

was implemented in 2010, consisting of telephone calls, outpatient

appointments and home visits. If a patient failed to attend either of the

scheduled outpatient appointments they would receive a telephone call from the

dietetic assistant to review self-reported weight status and intake. Patients with

suboptimal intake or weight loss were visited at home by the study dietitian in

lieu of the missed scheduled outpatient appointment. This unique model of care

was able to achieve 100% follow-up of malnourished inpatients. There were

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significant improvements in mean weight, triceps skinfold thickness and

handgrip strength for patients receiving ANS, with three out of four improving

their SGA score. In addition, two-thirds of patients had improved quality of life

(QOL). This is consistent with previous studies reporting an improvement in

QOL following nutritional intervention in malnourished patients (Ravasco et al.,

2005b; Rufenacht et al., 2010).

There is evidence that intensive dietetic monitoring and follow-up results in

higher nutrient intake, and this is a plausible reason for the improvements in

outcomes seen in this study (Kwon et al., 2004). These results are noteworthy,

as improvement in nutritional status has been shown to reduce readmissions,

rate of complications and mortality, which may result in long term cost-savings

for the individual, health-care institution and government (Stratton et al., 2005;

Koretz et al., 2007; Norman et al., 2008a; Gupta et al., 2010; Somanchi et al.,

2011; Starke et al., 2011).

The ANS service allowed for one of three modes of follow-up in the first four

months post-discharge, namely telephone calls, outpatient visits and home visits

for patients who did not attend outpatient appointments. Telephone calls made

up almost three quarters of overall contacts and were predominantly

administered by a trained dietetics assistant. They are relatively low cost and an

efficient form of patient follow-up which appear to generate positive nutritional

outcomes for patients as shown in this study. Telephone calls are less time-

intensive than outpatient reviews, and thus offer the benefit of reduced

manpower requirements and reduced costs for the healthcare provider. The

dietetic assistant was trained to ask a set of questions regarding appetite,

supplement usage (if prescribed), and to identify any new dietary issues or

questions. Detailed documentation on the advice given during telephone calls

ensured continuity of care when the dietitian saw the patient at the next follow-

up. The standard questions and advice administered by the dietetics assistant

via telephone calls are included in Appendix F. From the telephone calls, we

were able to review patient’s nutritional intake, reinforce the advice given during

the previous dietetic consultation and remind patients to attend the next

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outpatient appointment with the dietitians. Patients who did not do well

nutritionally and missed their appointments were visited by the dietitian at their

homes. With this method, we were able to keep home visits (which is resource-

intensive) to patients who really needed it. To the best of our knowledge, there

have been no other studies that reserve home visits for this group of patients.

There are two studies published on the efficacy of combined outpatient visits

and telephone follow-up (Isenring et al., 2004; Neelemaat et al., 2011a) and one

study on home visits (Feldblum et al., 2010) to improve the nutritional outcomes

of malnourished patients discharged from hospital. These research were studies

conducted on geriatric population (Feldblum et al., 2010; Neelemaat et al.,

2011a) and oncology outpatients (Isenring et al., 2004). After the initiation of our

study, a pilot study on 12 patients was carried out to test the feasibility of

combined telephone follow-up and home visits on malnourished geriatric

patients (≥ 65 years old) discharged from the hospital (Mudge et al., 2012). As

the number of subjects was too small to provide any statistical significance, only

descriptive results were shared. The study provided “proof of concept” for post-

discharge nutritional management of malnourished patients using combined

telephone calls and home visits (Mudge et al., 2012).

Impact on Practice

This study provides promising initial evidence that a multi-modal ambulatory

nutrition support program is an effective way to follow-up malnourished hospital

patients post discharge, at relatively low cost and healthcare burden. The

Ambulatory Nutrition Support services arising from this research programme has

since been implemented as part of NUH Dietetics protocol for post-discharge

malnourished patients.

Strengths

There are a number of strengths for this study. It is the first study of its kind to

explore home visits for malnourished patients who did not attend follow-up and

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includes adult malnourished patients across the age and disease spectrums. It

is also the first study specific to the Singaporean population. Inter-rater

differences were not present in this study as one dietitian measured all

nutritional outcomes, and this dietitian was trained in the use of all measurement

tools. The study protocol required that the baseline measurements (body weight,

SGA, mid-arm anthropometry, handgrip strength and QOL) carried out were no

more than 4 days before patient discharge regardless of whether they had been

done earlier during the admission. This ensures the currency of the baseline

data as it has been widely reported that patients’ weight and nutrition status tend

to deteriorate during hospitalisation (McWhirter & Pennington, 1994;

Braunschweig et al., 2000; Norman et al., 2008b; Cansado et al., 2009).

Limitations

A major limitation of this study is the pre-post design and lack of a control group

due to the nature of the funding which was for quality improvement purposes.

Hence, we were not able to use the randomised controlled trial (RCT) design.

There were ethical concerns as to what interventions would the control group

receive if RCT was conducted. It is possible that contact with a health

professional may have been responsible for the observed improvements. The

different time period of each cohort may have resulted in comparisons that were

not equally matched. Although there was no statistically significant difference

between the demographics of each cohort, there may have been other

characteristics which differed, such as socioeconomic status, family situation or

motivation level. The cost to the patient associated with outpatient review, in

comparison to free-of-charge telephone calls and home visits, may have

negatively impacted outpatient attendance rates.

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8.2 RECENT DEVELOPMENTS

This section highlights recent relevant publications which post-date the

published papers arising from this thesis.

Malnutrition and outcomes Subsequent to the publication of our paper (Lim et al., 2012), a large multicentre

study (n=2982) conducted in the Australasian region has been published

(Agarwal et al., 2013). In this study, malnutrition was assessed using SGA on a

single day assigned as NutritionDay (Agarwal et al., 2013). Disease severity

was determined using Patient Clinical Complexity Level (PCCL) and controlled

for in the analyses. The PCCL is a complex scoring system based on DRG to

determine the cumulative effect of a patient’s complications and comorbidities

(Department of Health and Ageing: Australian Government.). Agarwal et al.

(2013) found that malnourished patients had almost twice the risk of in-hospital

mortality and significantly higher readmission rate (35%) within 90 days of index

hospitalisation compared to well-nourished patients (27%). The median LOS for

malnourished patients was also 1.5 times higher than well-nourished patients

(Agarwal et al., 2013) These findings confirm the detrimental effect of

malnutrition in hospitalised patients independent of the underlying disease and

its complexities. This paper showed that even with a different approach to

controlling for underlying disease and its complexities, there is clear evidence of

an independent impact of malnutrition on clinical outcomes. As such, these

results confirm and strengthen the work of this thesis.

Nutrition screening Post development and validation of 3-MinNS, the A.S.P.E.N. and the Academy

of Nutrition and Dietetics published a consensus statement which indicates that

a screening tool should include the identification of 2 or more of the following 6

characteristics to be used to diagnose malnutrition: 1) insufficient energy intake,

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2) weight loss, 3) loss of muscle mass, 4) loss of subcutaneous fat, 5) localized

or generalized fluid accumulation and 6) diminished functional status as

measured by handgrip strength. (White et al., 2012). Coincidentally, the 3-

MinNS contains 3 of the 6 characteristics recommended. As the 3-MinNS is a

nutrition screening tool and not a diagnostic tool, having 3 characteristics would

suffice to determine patients at risk of malnutrition. This consensus statement

therefore provides further support to the work done on 3-MinNS under this

research programme. As such, there is potential for 3-MinNS to be used in other

countries if validated in the population.

Two recent studies which compare various nutrition screening tools in older

medical inpatients highlight commonalities between the tools (Poulia et al.,

2012; Young et al., 2013). In the study by Young et al. (2013), the nutrition

screening tools tested were MST, MNA-SF, MUST, NRS 2002, SNAQ,

Simplified Nutritional Appetite Questionnaire and Rapid Screen, whereas Poulia

et al. (2012) tested on NRI, Geriatric Nutritional Risk Index (GNRI), MNA-SF,

MUST and NRS 2002. Although the studies were specific to elderly inpatients,

the results from these two studies show that in general, all screening tools (if

accurately and completely implemented) are able to perform their function well.

Therefore, it is recommended that healthcare professionals choose a validated

screening tool that best matches their patient population and which they find

easiest to implement in practice (Young et al., 2013).

A recent study carried out in Norway, showed that quality improvement

initiatives were able to improve the nutrition screening rates of patients (Tangvik

et al., 2012) . The proportion of patients screened by NRS 2002 increased

significantly from the first to the last survey, with a range of 54% to 77% (p =

0.012). However the proportion of patients at nutritional risk who received

nutritional treatment did not improve with implementation and only 5% of the

patients at nutritional risk were evaluated and followed up by a dietitian. The

implementation plans were limited to creating nutritional guidelines and a staff

network. The staff in the network were educated for 2 days in basic clinical

nutrition and were tasked to introduce the guidelines to their units. The results

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showed that besides implementing a nutrition screening protocol and involving

all the stake-holders, an effective quality improvement programme has to be

multi-pronged and continuous to ensure sustainable outcomes.

Post-discharge care For the continuity of care for malnourished patients post-discharge, a recent

study on 38 malnourished elderly patients (≥ 60 years) reported that only 45%

received nutrition intervention within 6 weeks post-discharge (Rasheed &

Woods, 2013a). Of the group receiving nutrition support, 24% of patients

improved in body weight and 59% lost weight despite receiving nutrition

intervention. This reinforced an urgent need for a programme similar to our

Ambulatory Nutrition Support (ANS) service. With ANS, we managed to achieve

100% (n = 163) follow-up of malnourished patients post hospital discharge and

of these, an encouraging 70% gained weight in addition to significant

improvement in nutrition status, functional status and quality of life (Lim et al.,

2013b).

General comments

The conceptual framework in this thesis aligned with a recent recommendation

of a novel care model by the interdisciplinary Alliance to Advance Patient

Nutrition comprising of the Academy of Nutrition and Dietetics, the Academy of

Medical-Surgical Nurses, The American Society for Parenteral and Enteral

Nutrition, The Society of Hospital Medicine and Abbott Nutrition, to better

address hospital malnutrition (Tappenden et al., 2013). It emphasised 6

principles: (1) create an institutional culture where all stakeholders value

nutrition, (2) redefine clinicians' roles to include nutrition care, (3) recognize and

diagnose all malnourished patients and those at risk, (4) rapidly implement

comprehensive nutrition interventions and continued monitoring, (5)

communicate nutrition care plans, and (6) develop a comprehensive discharge

nutrition care and education plan. Prior to the research programme, NUH

Dietetics Department had already put in place a system to communicate

217


nutrition care plans with other healthcare professionals; especially the doctors,

nurses and caregivers (item 5 of the recommendation). This research

programme has successfully addressed principles 1, 3, 4 and 6.

Item 2 in redefining clinician’s roles in nutrition care is challenging due to

professional silos and existing busy clinical workloads. However the publications

arising from this research programme have created multiple platforms to share

the results with clinicians and in local conferences. In addition, media interests

from the national newspapers (see page 18) on this research programme have

helped to raise awareness among the public and healthcare professionals.

These led to better awareness among clinicians on the importance to manage

malnutrition, with a few collaborations already taking place in Singapore, such

as the setting up of a Nutrition Support Team comprising doctors, dietitians and

pharmacists, ‘blanket referral’ to dietitians for patients in the Intensive Care Unit

and implementing nutrition screening in other institutions.

In summary, the recent papers are in agreement with the work and results of the

research conducted under this PhD programme. Taken together, this PhD

research and the work of others have further built up the scientific knowledge

base and added value to current evidence-based practice in the screening and

management of at risk and malnourished patients.

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8.3 RECOMMENDATIONS

Arising from the results and outcomes of this research programme, these are

the recommendations proposed in the areas of clinical practice, education and

research.

8.3.1 Clinical practice

• It is imperative to recognise the significant prevalence and consequences of

malnutrition in hospitalised patients.

• Malnutrition must be identified and treated concurrently with management of

a patient’s medical condition.

• All hospitalised patients should be screened for malnutrition using a valid,

reliable, efficient tool relevant to the population on which it is used. The 3-

MinNS screening tool is recommended for use on Singaporean adult

inpatients.

• Validity and reliability studies of a screening tool should ideally be carried out

with the intended assessors (usually nurses) in a blinded manner.

• Compliance with nutrition screening, including completion rate, accuracy

(whether the tool is being used correctly) and referral rate for at risk patients

should be evaluated annually, at least.

• If the audit results are undesirable, it is recommended to carry out quality

improvement activities to find out the root cause for the non-compliance to

nutrition screening and work collaboratively towards overcoming the

problems identified.

• It is possible to achieve nutrition screening compliance rate of above 90%

with quality improvement initiatives effectively implemented. More

importantly, the positive results should be sustained through organisation

and system support.

219


• Any patient identified as malnourished or at risk of malnutrition on screening

should be referred to the dietitians for nutrition assessment and nutrition

intervention as required. Creating an online referral system between the

professionals responsible for screening (nurses) and those responsible for

assessment (dietitians) could streamline this process.

• Close collaboration between Dietetics, Nursing and Clinical Departments is

important to ensure continuous improvement and that the process of

screening, referral, intervention and monitoring are streamlined and adhered

to for the benefit of patients.

• Post-discharge follow-up of malnourished patients is critical for monitoring

the effectiveness of inpatient nutrition intervention due to the short length of

hospital stay. Hence, community-based intervention and follow-up is a

feasible option for treating and preventing malnutrition. A model of follow-up

that includes outpatient review, telephone calls and home visits for patients

who do not attend outpatient appointments is effective in following up these


8.3.2 Education

• Professional development education and/or orientation for healthcare

workers should include increasing the awareness of the prevalence and

impact of malnutrition.

• Training in the implementation of nutrition screening should be incorporated

into orientation programmes for nurses and dietitians to ensure accurate

administration of screening and appropriate referral of patients. Periodic

refresher courses should be offered to existing staff to maintain competency.

• The ongoing quality initiatives and results of the compliance to nutrition

screening should be incorporated into training programmes for nurses and

dietitians.

220


• Dietitians on ward duties should capitalise on educational opportunities by

providing immediate feedback to nursing staff who have incorrectly

completed nutrition screening.

• Malnourished patients and families or their caregivers need education to

understand their condition and be provided with resources and advice on

how to overcome malnutrition. The education on nutrition has to be targeted

and individualised.

• Dietitians play an important role in empowering patients and caregivers to

manage malnutrition, and to rally family support for patients so as to

encourage them to be compliant with nutritional advice and treatment.

• Close follow-up post hospitalisation is important to reinforce the education

that has been given to the patients, adjust treatment and to clarify any

misconception.

8.3.3 Research

• Randomised controlled trials could be carried out to compare the

effectiveness of Ambulatory Nutrition Support services versus conventional

follow-up of malnourished patients via outpatient visits. These should include

robust cost analysis as well as cost feasibility if incorporate into practice.

• Research investigating the prevention and management of malnutrition in the

outpatient or community settings in Singapore may be warranted as a first

step in reducing the prevalence of malnutrition in newly admitted hospital

patients. This may include nutrition screening at the community level and

treating those who are at risk or already malnourished before they

deteriorate further and require admission to the hospital.

• There could be further study on the feasibility of electronic medical records to

facilitate data entry for nutrition screening and auto-referral of ‘at-risk’ cases

to the dietitians.

221


• It may also be worthwhile to study the feasibility of using electronic medical

records to overcome incompletion of screening by making it compulsory to

enter the nutrition screening field before allowing the user to continue.

• As 3-MinNS has spread to nursing homes, it is recommended that a

validation study be carried out in this setting.

• Research could be carried out to determine if the 3-Minute Nutrition

Screening Tool can be used in the community to identify malnourished or ‘at

risk’ individuals in this setting. This may facilitate early intervention, prevent

the individual from further nutrition deterioration and avert hospitalization.

• A randomised control trial could be conducted to determine if nutritional

intervention in the community can help prevent malnutrition in the first place,

leading to avoidance or reduction in hospitalisation.

222


8.4 CONCLUSION AND CONTRIBUTION TO KNOWLEDGE

This research programme has addressed a wide range of gaps in current

literature. It has made a significant contribution to the body of knowledge,

especially in Singapore, in the areas of malnutrition and its impact on outcomes,

nutrition screening, and improving dietetics support services for malnourished

patients. It has addressed the research questions that were set forth in the

beginning.

Malnutrition is a significant issue in Singapore, with almost one third of adult

patients malnourished on admission to hospital (RQ1). This has a significant

impact on clinical outcomes, resulting in longer length of stay, higher rates of

readmission and mortality, and greater healthcare costs (RQ1). The first critical

step in effective management of malnutrition is the use of nutrition screening to

accurately identify patients who are malnourished or at risk of malnutrition. The

3-MinNS is a quick, efficient and valid tool for nutrition screening of adult

inpatients in Singapore. It is able to identify patients requiring further nutrition

assessment and to differentiate between moderate and severe malnutrition

(RQ2). Most importantly, it is valid and reliable when administered by nursing

staff, the intended users of the tool (RQ3). Audits conducted post hospital-wide

implementation of 3-MinNS revealed fairly high rates of error and incompletion,

and failure to refer some cases for nutrition assessment (RQ4). Quality

improvement initiatives can successfully reduce error and incompletion rates,

and ensure appropriate referral of patients at nutritional risk (RQ4). Effective and

accurate nutrition screening and referral of appropriate patients are critical first

steps in the management of malnutrition, but given the short duration of most

inpatient admissions, post-discharge management strategies are critical to

holistically manage these patients. Many patients became lost to follow-up in

the traditional outpatient dietetic review model (RQ5). Conversely, an

Ambulatory Nutrition Support service is able to effectively follow-up patients

223


post-discharge, and results in improvements in nutritional and quality of life

outcomes (RQ5).

This research programme is amongst the first to examine the impact of

malnutrition on length of hospital stay, readmission, hospitalisation cost and

mortality in a large sample representative of patients admitted to a major

Singaporean tertiary hospital. It has provided clear evidence that the adverse

outcomes of malnutrition are not just a consequence of the disease process,

and lead to substantial increases in length of hospital stay, readmission rate,

mortality and hospitalisation cost when compared with well-nourished patients of

similar diagnoses and complexities. The research programme led to the

development and validation of a new nutrition screening tool (3-MinNS) and

confirmed that the 3-MinNS is a valid and reliable nutrition screening tool to be

used in Singaporean acute hospitals. Quality improvement methods employed

proved successful in improving the compliance of nurses to 3-MinNS and

ensuring referral of malnourished or ‘at risk’ patients to dietitians. Finally, this

research programme has provided an evidence-based and effective method for

following up malnourished patients post-discharge, which resulted in improved

nutritional status of these patients.

In conclusion, the findings from the research programme have contributed to

positive changes in the nutrition screening process and the perception and

management of malnutrition in Singapore. It has contributed important new

knowledge and has demonstrated that it is possible to change practice in a large

and complex organisation employing thousands of staff, with many stakeholders

involved. Furthermore, this research programme has successfully delivered a

comprehensive model for managing hospital malnutrition, from screening on

admission and referral for assessment, to intervention and post-discharge

follow-up. Through these initiatives, we hope that many patients with or at risk of

malnutrition will receive the quality of care they need and deserve, leading to

improved outcomes and better quality of life.

224


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Appendix A

Source: Lim SL, et al. Asia Pac J Clin Nutr 2009; 18:395-403.

248


Appendix B

Source: Detsky AS, et al. J Parenter Enteral Nutr 1987; 11:8-13.

249


Appendix C 7-Point Subjective Global Assessment

R A T I N GS (circle one rating for each category)

Weight loss ____ kg in the past 6 months 7 6 5 4 3 2 1

Dietary Intake (past 2 weeks) 7) Good (Full share of usual meal) 6) Good (> ¾ - 1 share of usual meal) 5) Borderline (½ – ¾ share of usual meal) but increasing 4) Borderline (½ – ¾ share of usual meal), no change or decreasing 7 6 5 4 3 2 1 3) Poor (< ½ share of usual meal) but increasing 2) Poor (< ½ share of usual meal) no change/decreasing 1) Starvation (<¼ of usual meal)

Gastrointestinal symptoms (that persisted for > 2 weeks) Nausea: _____ Vomiting: ______ Diarrhoea: _______ 7) No symptom 6) Very few intermittent symptoms (1x per day) 7 6 5 4 3 2 1 5) Some symptoms (2-3x per day) - improving 4) Some symptoms (2-3x per day) – no change 3) Some symptoms (2-3x per day) – getting worse 1-2) Some/all symptoms (> 3x per day) Functional status (nutrition related) 6-7) Full functional capacity 3-5) Mild to moderate loss of stamina 7 6 5 4 3 2 1 1-2) Severe loss of functional ability (bedridden) Disease state affecting nutritional requirements 6-7) Little or no increase in metabolic demand (no or low stress) 3-5) Mild to moderate increase in metabolic demand (moderate stress) 7 6 5 4 3 2 1 1-2) Drastic increase in metabolic demand (high stress) Muscle wastage: 6-7) Little or no depletion in all areas (at least 3 areas) 3-5) Mild to moderate depletion 7 6 5 4 3 2 1

1-2) Severe depletion Fat stores 6-7) Little or no depletion in all areas

3-5) Mild to moderate depletion 7 6 5 4 3 2 1 1-2) Severe depletion

Oedema: 6-7) Little or no oedema (nutrition related) 3-5) Mild to moderate oedema 7 6 5 4 3 2 1 1-2) Severe oedema Nutritional Status: Well Nourished / Mildly to Moderately Malnourished / Severely Malnourished Overall SGA Rating: 7 6 5 4 3 2 1 (circle one)

Ratings Weight loss 7 <1kg 6 <3% 5 3-<5% 4 5-<7% 3 7-<10% 2 10-<15% 1 ≥15%

If ↑ weight trend, add 1 point, if ↓ weight trend within 1 month, minus 1 point

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Appendix D Euro Quality of Life–5 Domain and Visual Analogue Scale

Mobility

I have no problems in walking about

I have some problems in walking about

I am confined to bed Self-Care

I have no problems with self-care

I have some problems washing or dressing myself

I am unable to wash or dress myself Usual Activities (e.g. work, study, housework, family or leisure activities)

I have no problems with performing my usual activities

I have some problems with performing my usual activities

I am unable to perform my usual activities Pain/Discomfort

I have no pain or discomfort

I have moderate pain or discomfort

I have extreme pain or discomfort Anxiety/Depression

I am not anxious or depressed

I am moderately anxious or depressed

I am extremely anxious or depressed

© 2003 EuroQol Group. EQ-5D™ is a trade mark of the EuroQol Group

251


To help people say how good or bad a health state is, we have drawn a scale (rather like a thermometer) on which the best state you can imagine is marked 100 and the worst state you can imagine is marked 0. We would like you to indicate on this scale how good or bad your own health is today, in your opinion. Please do this by drawing a line from the BLACK BOX below to whichever point on the scale indicates how good or bad your health state is today.

© 2003 EuroQol Group. EQ-5D™ is a trade mark of the EuroQol Group

9 0

8 0

7 0

6 0

5 0

4 0

3 0

2 0

1 0

100

Worst imaginable health state

0

Best imaginable health state

Your own health state

today

252


Appendix E

Paper on 7-point Subjective Global Assessment

253

Paper submitted to Clinical Nutrition (not part of PhD research programme)

7-point Subjective Global Assessment is more time sensitive than conventional

Subjective Global Assessment in detecting nutritional changes

Su Lin Lim1,2, Xiang Hui Lin1, Lynne Daniels2

1Dietetics Department, National University Hospital, Singapore,

2School of Exercise and Nutrition Sciences, Queensland University of Technology,

Australia

ABSTRACT

Background & aims: It is important for nutritional intervention in malnourished

patients to be guided by accurate evaluation and detection of small changes in the

patient’s nutritional status over time. However, the current Subjective Global

Assessment (SGA) is not able to detect changes in a short period of time. The aim of

the study was to determine whether 7-point SGA is more time sensitive to nutritional

changes than the conventional SGA.

Methods: In this prospective study, 67 adult inpatients assessed as malnourished

using both the 7-point SGA and conventional SGA were recruited. Each patient

received nutrition intervention and was followed up by a dietitian post-discharge.

Patients were reassessed using both tools at 1, 3 and 5 months from baseline

assessment.

Results: It took significantly shorter time to see a one-point change using 7-point

SGA compared to conventional SGA (median: 1 month vs. 3 months, p = 0.002). The

likelihood of at least a one-point change is 6 times greater in 7-point SGA compared

to conventional SGA (odds ratio = 6.23, 95% CI 2.73-14.2, p<0.001). Changes were

observed in 75% of patients using 7-point SGA vs. 42% using SGA. Fifty-six percent

of patients who had no change in SGA score had changes detected using 7-point

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SGA. The level of agreement between two blinded assessors for 7-point SGA was

83% (k=0.726, p<0.001).

Conclusions: The 7-point SGA is more time sensitive in its response to nutritional

changes than conventional SGA. It can be used to guide nutritional intervention for

patients.

Keywords:

7-point Subjective Global Assessment; Nutrition status; Malnutrition; Nutritional

changes; Intervention

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1. Introduction

Malnutrition is prevalent in hospitals and leads to adverse outcomes.1-3 Studies

have shown that patient outcomes can be improved with nutrition support.4,5

Nutritional intervention must be guided by accurate evaluation and detection of small

changes in the patient’s nutritional status over time. Subjective Global Assessment

(SGA) is a well validated tool widely used to assess nutritional status of patients.6-8 It

involves assigning a rating of A, B or C for each of eight components: weight and

dietary intake changes, gastrointestinal symptoms, functional capacity, metabolic

stress from disease, muscle wasting, fat depletion and nutrition-related edema.6 The

final rating of SGA is a subjective summation of the eight components to classify

patients into three categories; A: well nourished, B: moderately malnourished and C:

severely malnourished.6 Despite widespread use of SGA for nutritional assessment,

very few studies have used this tool to assess changes in nutritional status over time.9

Interventional studies using SGA usually showed no significant change between the

pre and post results.10 An important factor may be the considerable time lag before

changes in nutritional status are detected using SGA score. Given the well-established

association between malnutrition and increased risk of morbidity and mortality,1-3

monitoring changes in nutritional status is vital, especially in patients who have

already been assessed as malnourished or those at risk of further nutritional

deterioration.

The 7-point SGA was developed for use on 680 patients commencing

peritoneal dialysis in the CANUSA Study.11 Similar to SGA, the overall rating of 7-

point SGA is subjective, but the scale is expanded to 7 points where a rating of 1-2

indicates an individual is severely malnourished, 3-5 moderately malnourished and 6-

7 well nourished. Therefore, the categories of nutrition status as assessed by the 7-

256


point scale are consistent with conventional SGA, i.e. well nourished, moderately

malnourished or severely malnourished. The CANUSA study showed that a one unit

lower in the 7-point SGA score was prospectively associated with a 25% increase in

the relative risk of death.11

Since the CANUSA Study, there has been increased use of 7-point SGA,

however this has been limited to renal patients.12-14 No studies have reported on the

use of 7-point SGA in other patient groups. Some authors have speculated that 7-point

SGA may be more sensitive than the conventional SGA in identifying small changes

in renal patients’ nutritional status;14,15 however this is yet to be confirmed in studies.

Given the broad nature of a 3-point rating in the conventional SGA, a substantial

improvement in nutritional status may be required before patient transitions from a

‘B’ (moderately malnourished) to an ‘A’ (well nourished) rating. In contrast, when

using 7-point SGA a moderately malnourished patient may improve from a rating of 3

to 4. In this instance, the patient is still classified as moderately malnourished, but

smaller changes in nutritional status may be detected. Valid improvements in score

within a broad category would suggest improved nutritional status, and conversely

any deterioration in status can be detected and addressed quickly. To date, no studies

have been published to support this opinion.

The aim of the study was to determine if 7-point SGA is more time sensitive

in its response to nutritional changes than conventional SGA across different patient

diagnostic groups.

257


2. Methods

2.1. Screening and Study Participants

All patients were screened for risk of malnutrition on admission using 3-

Minute Nutrition Screening16,17 by the ward nurses as per hospital protocol. Any

patient identified as at risk of malnutrition was referred to the hospital dietitian, who

confirmed the diagnosis of malnutrition using SGA6 and provided individualized

nutrition intervention and counseling on the ward. Consecutive malnourished adult

patients aged ≥ 21 years of age were recruited for the study. Psychiatry patients,

maternity patients, patients on palliative care and patients discharged to a nursing

home or community hospital were excluded from the study. The National Healthcare

Group Domain Specific Review Board approved the study protocol. Informed written

consent was obtained from each participant.

2.2. Baseline assessments

For the purpose of this study, nutritional status was re-assessed using

conventional SGA and 7-point SGA by a study dietitian no more than four days

before the patient was discharged from hospital, and this was considered as baseline

for tracking the nutritional status of patients post-discharge. For better standardization

among assessors, 7-point SGA (Figure 1) was modified from the one used in the

CANUSA Study11 to include a selection of ratings within each component. At the

same sitting, patient’s body weight, handgrip strength18 and assessment of quality of

life using the Euro Quality of Life - Visual Analogue Scale (EQ-VAS)19 were

measured.

258


Inter-rater agreement between the two study dietitians was conducted on 37

patients using 7-point SGA. The first dietitian assessed each patient using 7-point

SGA, followed by a second dietitian who repeated the 7-point SGA assessment and

was blinded to the results of the first dietitian.

2.3. Follow-up assessments

A total of 67 patients were recruited for this study. Each was provided with

follow-up appointments at an outpatient clinic 1 month, 3 months and 5 months post

discharge from hospital. During these follow-up visits, patients were reassessed using

7-point SGA and conventional SGA. All patients were given individualized nutrition

intervention and counseling as appropriate by the study dietitian. Patients who failed

to turn up for scheduled outpatient appointments were home-visited by the study

dietitian within one week of the missed appointments. At the fifth month follow-up,

assessment using 7-point SGA and conventional SGA was carried out by a second

dietitian who was blinded to the results of the previous ratings. Patient’s body weight,

handgrip strength and assessment of quality of life using the EQ-VAS were also

measured. The study workflow is presented in Figure 2.

2.4. Statistical analyses

All statistical analyses were performed using the Statistical Package for the

Social Sciences for Windows (version 19.0, SPSS Inc., Chicago, IL, USA) with

statistical significance set at p < 0.05. Pearson’s chi-square test was used to compare

the likelihood of detecting a change between 7-point SGA and conventional SGA

presenting the results as odds ratio at 95% confidence intervals (CI). Wilcoxon Signed

Ranks test was performed to determine the time to see a minimum one-point change

in both 7-point SGA and conventional SGA and reported as median. Spearman’s rho

259


was used to determine the correlation between changes in both SGAs and changes in

body weight, handgrip strength and EQ-VAS. The inter-rater agreement between the

two assessors using 7-point SGA was reported as % agreement and Kappa statistics.

260


Figure 1: 7-point Subjective Global Assessment (7-point SGA)

R A T I N GS (circle one rating for each

category) Weight loss ____ kg in the past 6 months 7 6 5 4 3 2 1

Dietary Intake (past 2 weeks) 7) Good (Full share of usual meal) 6) Good (> ¾ - 1 share of usual meal) 5) Borderline (½ – ¾ share of usual meal) but increasing 4) Borderline (½ – ¾ share of usual meal), no change or decreasing 7 6 5 4 3 2 1 3) Poor (< ½ share of usual meal) but increasing 2) Poor (< ½ share of usual meal) no change/decreasing 1) Starvation (<¼ of usual meal)

Gastrointestinal symptoms (that persisted for > 2 weeks) Nausea: _____ Vomiting: ______ Diarrhoea: _______ 7) No symptom 6) Very few intermittent symptoms (1x per day) 7 6 5 4 3 2 1 5) Some symptoms (2-3x per day) - improving 4) Some symptoms (2-3x per day) – no change 3) Some symptoms (2-3x per day) – getting worse 1-2) Some/all symptoms (> 3x per day) Functional status (nutrition related) 6-7) Full functional capacity 3-5) Mild to moderate loss of stamina 7 6 5 4 3 2 1 1-2) Severe loss of functional ability (bedridden) Disease state affecting nutritional requirements 6-7) Little or no increase in metabolic demand (no or low stress) 3-5) Mild to moderate increase in metabolic demand (moderate stress) 7 6 5 4 3 2 1 1-2) Drastic increase in metabolic demand (high stress) Muscle wastage: 6-7) Little or no depletion in all areas (at least 3 areas) 3-5) Mild to moderate depletion 7 6 5 4 3 2 1

1-2) Severe depletion Fat stores 6-7) Little or no depletion in all areas

3-5) Mild to moderate depletion 7 6 5 4 3 2 1 1-2) Severe depletion

Oedema: 6-7) Little or no oedema (nutrition related) 3-5) Mild to moderate oedema 7 6 5 4 3 2 1 1-2) Severe oedema Nutritional Status: Well Nourished / Mildly to Moderately Malnourished / Severely Malnourished Overall SGA Rating: 7 6 5 4 3 2 1 (circle one)

Ratings Weight loss 7 <1kg 6 <3% 5 3-<5% 4 5-<7% 3 7-<10% 2 10-<15% 1 ≥15%

If ↑ weight trend, add 1 point, if ↓ weight trend within 1 month, minus 1 point

261


Figure 2: Study workflow

Screening and Recruitment

Consecutive malnourished patients referred to the dietitians

Inclusion criteria:

≥ 21 years old

Malnourished as assessed by Subjective Global Assessment (SGA)

Not Psychiatry, Maternity and Palliative Care patients

Not patients discharged to nursing home or community hospital

Baseline Assessments

(n= 67)

7-point SGA and SGA conducted by the 1st dietitian

Body weight, handgrip strength, Quality of Life Visual Analogue Scale (EQ-VAS)

(all measurements were done at no more than 4 days before discharge from hospital)

Re-assessments

7-point SGA and SGA at 1-month, 3-month and 5-month post baseline

measurements

Body weight, handgrip strength and QoL VAS at 5-month post baseline

measurements

(All 5th month assessments were conducted by a 2nd dietitian, blinded to the

results of the previous measurements).

262


3. Results

The demographic profiles of the study subjects are described in Table 1. It took

significantly shorter time to see a one-point change using 7-point SGA compared to

conventional SGA (median: 1 month vs. 3 months, p = 0.002). The likelihood of at least a

one point change is 6 times greater using 7-point SGA compared to conventional SGA (Odds

Ratio: 6.23, 95% CI: 2.73-14.2, p <0.001).

Table 2 shows the frequency of the overall change in SGA score using 7-point SGA

and conventional SGA. Of the 39 patients that had no change in their score using

conventional SGA, 22 patients (56%) had a change in their score within the same nutritional

status category using 7-point SGA.

Table 3 compares the correlation between changes in both the 7-point and

conventional SGA and changes in body weight, handgrip strength and EQ-VAS. There is

moderate positive linear correlation between changes in 7-point SGA and weight change (r=

0.681, p <0.001) and mild positive linear correlation between changes in 7-point SGA and

changes in handgrip strength and EQ-VAS. The correlation between changes in conventional

SGA and weight change is mild (r=0.589, p<0.001) and only weak correlation were found

between changes in conventional SGA and handgrip strength and EQ-VAS.

The level of agreement between two assessors for 7-point SGA was good, at a rate of

83% (k=0.726, p<0.001).

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Table 1

Demographics of the study subjects at baseline (n= 67)

Variable n (%) Mean ± SD (Range) Age (years) 63.9+14.5 (27-87) Gender

Male

Female

30 (45)

37 (55)

Ethnicity

Chinese

Malay

Indian

Others

52 (78)

8 (12)

4 (6)

3 (4)

Baseline Nutritional Status1

Moderately malnourished

Severely malnourished

62 (93)

5 (7)

Specialty

General Surgery

General Medicine

Cardiology

Respiratory

Gastroenterology

Oncology

Endocrinology

Geriatrics

Orthopaedic

Nephrology

19 (28)

15 (22)

10 (15)

5 (8)

4 (6)

4 (6)

3 (4)

3 (4)

2 (3)

2 (3)

n= number; SD = standard deviation

1Severity of malnutrition as defined by Subjective Global Assessment

Table 2

Change in overall nutrition assessment score between baseline and the fifth month using 7-

point SGA and conventional SGA (n=67)

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Change in score between baseline and 5th

month

7-point SGA

n (%)

Conventional SGA

n (%)

0-point (no change) 17 (25) 39 (58)

1-point 30 (45) 28 (42)

2-point 15 (22) 0 (0)

3-point 5 (8) NA

Total patients with a change in score 50 (75) 28 (42)

SGA = Subjective Global Assessment

NA = Not applicable

265


Table 3

Correlation between changes in 7-point SGA and conventional SGA and changes in body

weight, handgrip strength and quality of life measures using Euro-Quality of Life - Visual

Analogue Scale (EQ-VAS) in 5 months

Changes observed between

baseline and 5th month

n Changes 7-point SGA Changes in

conventional SGA

Correlation p Correlation p

Weight change 67 0.681a <0.001* 0.589b 0.001*

Changes in handgrip

strength

59 0.346b 0.007* 0.210c 0.111

Changes in quality of life

(EQ-VAS)

55 0.369b 0.006* 0.124c 0.366

SGA = Subjective Global Assessment

*significant p value, aModerate correlation,

bMild correlation, cWeak correlation

266


4. Discussion

The current study has shown for the first time that 7-point SGA is able to detect

response to nutritional intervention faster than conventional SGA. It took significantly shorter

time to see a one-point change using 7-point SGA in comparison to conventional SGA. Our

study shows that even though there appears to be no change in classification using

conventional SGA, changes in score within the traditional categories using 7-point SGA were

observed in 56% of these patients. This is important as repeated measures of nutritional

assessment over time yields valuable information that might help guide the nature of the

dietary advice or intervention given. For example, if a patient was decreasing in nutritional

status over time, more aggressive nutritional therapy could be provided. From this current

study, we are able to show that 7-point SGA is a useful nutrition assessment tool in detecting

nutritional changes over relatively short periods of time when compared to conventional

SGA.

It is ironic that although SGA has been a widely validated and well accepted tool to

determine the nutritional status of patients,7,8 it has not been used in many studies to report

changes in nutritional outcomes. Even studies that use SGA initially do not report outcomes

using this tool.5 Instead, changes in body weight are most commonly cited in studies that

span over three months to determine changes in nutritional status of patients.4,20,21 This is

probably due to the limitation of conventional SGA, where it is often not able to detect

change in nutritional status in a shorter period of time even when weight change is present.

However, there are limitations to using weight change to monitor nutritional status, as

changes in body weight may be confounded by the alteration in body composition and fluid

retention commonly associated with illness.22,23 In addition, weight measurements pose

challenges in patients who are bed bound or old and frail. In an audit of 526 hospital

admissions, only 67% of the population had information on weight.24 Even in the clinical

267


research context, there are difficulties in obtaining complete weight and height data.25,26 In

clinical practice, unavailable weight record can be as high as 74-85%.25-27

Malnutrition has been shown to have numerous detrimental effects on health and

quality of life.1-3 To ensure appropriate nutrition care is provided, an in-depth assessment of a

patient’s nutritional status is needed, and SGA has been developed for this purpose.6

However, once nutrition intervention is implemented, tracking changes in nutritional status is

required to evaluate the effectiveness of the chosen intervention, and to prompt changes in

the treatment plan as required. The benefit of 7-point SGA is that it can potentially detect

comparatively small changes within the broader categories of nutritional status. A study by

Campbell et al. (2007) on patients with chronic kidney disease showed a difference in body

composition between the rating points of 7-point SGA (3, 4 and 5) within the same category

of nutrition status (SGA B).14 Using total body potassium, a gold-standard measure for body

cell mass, a linear increase in mean body cell mass from ratings 3 to 5 in 7-point SGA was

detected. This suggests that nutritional changes took place even though patients would still

have been considered moderately malnourished (rating ‘B’) within the broad categories of

conventional SGA.14

The detailed response options in 7-point SGA enable standardized scoring and

objectivity of the assessors within each item in the 7-point SGA. This may partly explain the

good inter-rater reliability of 7-point SGA between dietitians, despite the tool having seven

ratings of nutritional status. Previous studies on SGA have shown inter-rater reliability of

79% and 81%.7,8 The ambiguity in the conventional SGA is addressed in 7-point SGA,

whereby the expanded items in each component are specified clearly (Figure 1), thus

facilitating greater standardization between assessors. The clarity of 7-point SGA is enhanced

by clear instruction that functional status should be nutrition related and not the consequence

268


of a debilitating medical condition such as stroke, and that at least 3 muscle areas need to be

examined.

Similar to conventional SGA, the final rating in 7-point SGA is based on the

subjective weighting of the components to classify patients into 3 categories: well nourished,

moderately malnourished and severely malnourished. Hence, 7-point SGA can always be

converted to conventional SGA rating (but not vice-versa). With this, the prognostic validity

of 7-point SGA remains the same as conventional SGA, which has been shown to have good

prognostic value for a range of clinical outcomes.1,3

The current study shows that changes in 7-point SGA better correlates with changes

in body weight, handgrip strength and quality of life (QoL) measures than conventional SGA.

Body weight, handgrip strength and QoL are commonly used as outcome measures for

nutrition intervention in malnourished patients.4,5 However, as each of these parameters on its

own cannot be used as a sole marker of malnutrition, the ability of 7-point SGA to diagnose

malnutrition as well as to monitor the nutritional progress of patients is notable.

There are several strengths in this study. This is the first study to show that 7-point

SGA can be used to detect nutritional changes faster than conventional SGA. This facilitates

earlier evaluation of the impact of any nutrition intervention, and provides critical guidance to

the healthcare professional in making decisions regarding medical nutrition therapy. Another

strength of this study is the use of a blinded assessor method to test the inter-rater reliability

of 7-point SGA.

In addition, this study was carried out across a broad range of medical conditions and

age groups. In contrast, 7-point scale SGA introduced in the CANUSA study11 has only been

studied in renal patients.12-14 The inclusion of a broad range of medical conditions is

advantageous as patients usually present with multiple comorbidities. Furthermore, it is not

practical to switch from one tool to another for different medical conditions. The aim is to

269


minimize confusion among staff, standardize practice and conserve resources in training staff

when they transfer from one ward to another. This study also showed that it is feasible to use

7-point SGA on patients from all adult age groups. In acute care hospitals, it is not practical

to have different nutrition assessment tools for different adult age groups. For example, Mini

Nutritional Assessment (MNA) has been developed for use on the elderly.28 This tool has

been validated and is frequently used in nursing homes and long term care facilities, and in

these settings has served its purpose well.28-30 Having such a targeted tool may be more

sensitive to the needs of the specific population. However in the hospital setting where there

is a wide age range of patients, it is not practical to carry out MNA on the elderly and use a

separate tool for younger adult patients.

As the same dietitian assessed 7-point SGA during the baseline measurement and at 1

month and 3 months post discharged, observer bias is a limitation of this study. To overcome

this limitation, the fifth month assessment was carried out by a second dietitian blinded to the

previous ratings in the sequential measures of 7-point SGA. Another limitation of our study is

that confounders such as age may have influenced the assessment of nutritional status using

either tool. However, this has been minimized as the trained study dietitians undergo yearly

competency assessments on the use of 7-point SGA and conventional SGA.

270


5. Conclusions

The 7-point SGA is more time sensitive in its response to nutritional changes than

conventional SGA. It can be used in a broad range of medical conditions and adult age

groups to assess and monitor the progress of nutritional status in patients. More importantly,

it can be used to guide nutritional intervention for patients.

Acknowledgements

We are very grateful to Linda McCann for providing advice and initial training on 7-point

Subjective Global Assessment.

Statement of authorship

SLL conceptualized, designed and conducted the study, interpreted the data and wrote

the manuscript. XHL conducted the study, analyzed and interpreted the data and wrote the

manuscript. LD provided significant advice on the design of the study and assisted in writing

the manuscript. All authors have made substantial contributions and approved the final

manuscript.

Conflict of interest

None of the authors had any conflict of interest related to the authorship of the

submitted paper.

Statement of funding

The study was supported by a grant from the Healthcare Quality Initiative and

Innovation Fund (HQI2F).

271


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Appendix F

Standard questions and advice given by the dietetics assistant via telephone follow-up as part of

Ambulatory Nutrition Support Service Before calling the patient, the dietetics assistant needs to read the nutritional documentation by the dietitians and understand what have been advised previously. Standard Questions: 1. Diet history (Breakfast, lunch, dinner, supper, snacks) 2. Are you consuming the nutrition supplements prescribed by

your dietitian? 3. How is your appetite? Has there been any recent loss of

appetite? 4. Has there been any loss of weight since you were last seen by

the dietitian? 5. Are there any other issues with regards to your diet? 6. Are there any questions on your diet? Standard Advice: 1. Add 1-2 teaspoons of oil into food (e.g. porridge, soup) 2. Follow the meal plan given by your dietitian 3. Include egg (whole/whites) for breakfast 4. Spread margarine/peanut butter thickly on breads 5. Take nourishing fluids (e.g. fruit juice, milkshake) 6. Add 1-2 teaspoons of margarine into piping hot rice 7. Change cooking methods (pan fry or deep fry instead of

boiling) 8. Supplement with ½ or 1 can or packet of nutrition supplement if

taking only less than 1/2 share meal. (Nutrition supplement would usually have been prescribed during the last visit by the dietitian)

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Appendix G Research Grant

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* The above grant was subsequently topped up to S$153,000

278


Appendix H NHG Domain-Specific Review Board Approval (Singapore)

279


280


281


282


283


Appendix I QUT Human Research Ethics Committee Approval

284


285


From: QUT Research Ethics Unit Sent: Friday, August 17, 2012 9:43 AM To: Su Lin Lim; Lynne Daniels; Maree Ferguson Cc: Janette Lamb Subject: Ethics Application Approval – 1200000301 Dear Ms Su Lin Lim Project Title: Nutrition status and clinical outcomes of patients receiving nutrition support in a tertiary hospital in Singapore Ethics Category: Human - Low Risk Approval Number: 1200000301 Approved Until: 17/08/2015 (subject to receipt of satisfactory progress reports) We are pleased to advise that your application has been reviewed by the Chair, University Human Research Ethics Committee (UHREC), and confirmed as meeting the requirements of the National Statement on Ethical Conduct in Human Research (2007). I can therefore confirm that your application is APPROVED. If you require a formal approval certificate, please respond via reply email and one will be issued. CONDITIONS OF APPROVAL Please ensure you and all other team members read through and understand all UHREC conditions of approval prior to commencing any data collection: > Standard: Please go to www.research.qut.edu.au/ethics/humans/stdconditions.jsp > Specific: None apply Decisions related to low risk ethical review are subject to ratification at the next available UHREC meeting. You will only be contacted again in relation to this matter if UHREC raises any additional questions or concerns. Whilst the data collection of your project has received QUT ethical clearance, the decision to commence and authority to commence may be dependent on factors beyond the remit of the QUT ethics review process. For example, your research may need ethics clearance from other organisations or permissions from other organisations to access staff. Therefore the proposed data collection should not commence until you have satisfied these requirements. Please don't hesitate to contact us if you have any queries. We wish you all the best with your research. Kind regards Janette Lamb on behalf of the Chair UHREC Research Ethics Unit | Office of Research | Level 4 88 Musk Avenue, Kelvin Grove | Queensland University of Technology p: +61 7 3138 5123 | e: [email protected] | w: www.research.qut.edu.au/ethics/

286

https://outlook.qut.edu.au/OWA/redir.aspx?C=a0CJlG8II0GjzYMMgnBObHDY8LJzUtBINMYkf4iBTpdlx3fjB__oQSrbBDUACuOfkFJSzMLqwAg.&URL=http%3a%2f%2fwww.research.qut.edu.au%2fethics%2fhumans%2fstdconditions.jsp�

https://outlook.qut.edu.au/OWA/redir.aspx?C=a0CJlG8II0GjzYMMgnBObHDY8LJzUtBINMYkf4iBTpdlx3fjB__oQSrbBDUACuOfkFJSzMLqwAg.&URL=http%3a%2f%2fwww.research.qut.edu.au%2fethics%2f�


From: QUT Research Ethics Unit Sent: Friday, March 22, 2013 2:49 PM To: Lynne Daniels; Su Lin Lim Cc: Janette Lamb Subject: Ethics Application Approval - 1200000602 Dear Ms Su Lin Lim Project Title: Development of novel approaches to improve the nutritional status of malnourished patients discharged from hospital and evaluation of its effectiveness Ethics Category: Human - Low Risk Approval Number: 1200000602 Approved Until: 22/03/2016 (subject to receipt of satisfactory progress reports) We are pleased to advise that your application has been reviewed by the Chair, University Human Research Ethics Committee (UHREC) and confirmed as meeting the requirements of the National Statement on Ethical Conduct in Human Research (2007). I can therefore confirm that your application is APPROVED. If you require a formal approval certificate please respond via reply email and one will be issued. CONDITIONS OF APPROVAL Please ensure you and all other team members read through and understand all UHREC conditions of approval prior to commencing any data collection: > Standard: Please see attached or go to www.research.qut.edu.au/ethics/humans/stdconditions.jsp > Specific: None apply Decisions related to low risk ethical review are subject to ratification at the next available UHREC meeting. You will only be contacted again in relation to this matter if UHREC raises any additional questions or concerns. Whilst the data collection of your project has received QUT ethical clearance, the decision to commence and authority to commence may be dependent on factors beyond the remit of the QUT ethics review process. For example, your research may need ethics clearance from other organisations or permissions from other organisations to access staff. Therefore the proposed data collection should not commence until you have satisfied these requirements. Please don't hesitate to contact us if you have any queries. We wish you all the best with your research. Kind regards Janette Lamb on behalf of the Chair UHREC Research Ethics Unit | Office of Research | Level 4 88 Musk Avenue, Kelvin Grove | Queensland University of Technology p: +61 7 3138 5123 | e: [email protected] | w:www.research.qut.edu.au/ethics/

287

http://www.research.qut.edu.au/ethics/humans/stdconditions.jsp�

mailto:[email protected]�

http://www.research.qut.edu.au/ethics/�


Appendix J Statement of Contributions of Co-Authors

288

Statement of Contribution of Co-Authors forThesis by Published Paper

The authors listed below have certified* that:

1. they meet the criteria for authorship in that they have participated in the conception,execution, or interpretation, of at least that part of the publication in their field of expertise;

2. they take public responsibility for their part of the publication, except for the responsibleauthor who accepts overall responsibility for the publication;

3. there are no other authors of the publication according to these criteria;

4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the editor orpublisher of journals or other publications, and (c) the head of the responsible academicunit, and

5. they agree to the use of the publication in the student's thesis and its publication on theAustralasian Research Online database consistent with any limitations set by publisherrequirements.

Publication title and date of publication or status:Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-yearmortality. Clinical Nutrition 2012; 31 (3):345-350.

Contributor Statement of contribution*

Lim Su Lin

J~jL) conceptualized, designed and conducted the study, interpreted~ the data and wrote the manuscript.Signature5 AUj\!isf ~o13

DateAlProf. Benjamin Ong provided significant advice on the design of the study and input

into manuscriptDr Chan Yiong Huak performed statistical analysis and interpreted the data

Dr Loke Wai Chiong provided significant advice on the design of the study and inputinto manuscript

Dr Maree Ferguson provided significant advice on the design of the study and inputinto manuscript

Prof. Lynne Daniels interpreted the data, provided significant advice on the design ofthe study and input into manuscript

Principal Supervisor ConfirmationI have sighted email or other correspondence from all Co-authors confirming their certifyingauthorship.

Prof. Lynne DanielsName

frto7O/SDa e

289








Publication title and date of publication or status:

Reply - Malnutrition and its impact on cost of hospitalisation, length of stay, readmission and 3-year mortality. Clinical Nutrition 2013; 32(3):489-490.

Contributor Statement of contribution*Lim Su Lin

~ wrote the reply letter to the editorSiqnature

5 A ~lAsf.2AJ1JDate

Prof. Lynne Daniels assisted in writing the reply letter to the editor

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors confirming their certifyingauthorship.


290



1. they meet the criteria for authorship in that they have participated in the conception, execution, orinterpretation, of at least that part of the publication in their field of expertise;

2. they take public responsibility for their part of the publication, except for the responsible author whoaccepts overall responsibility for the publication;


4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the editor or publisher ofjournals or other publications, and (c) the head of the responsible academic unit, and

5. they agree to the use of the publication in the student's thesis and its publication on the AustralasianResearch Online database consistent with any limitations set by publisher requirements.


Development and validation of 3-Minutes Nutrition Screening (3-MinNS) Tool for acute hospital patients inSingapore. Asia Pacific Joumal of Clinical Nutrition 2009;18(3):395-403.


Lim Su Lin

1~ conception of the research design and planning of study, data collection,recruitment of the participants, compilation, analysis and interpretation of

Signature the data, and writing of the manuscript5 ~'-1JtA rf :to13

DateTong Chung Van assisted in the collection of data

Dr Emily Ang involved in the research design and commented on the manuscript

A/Prof. Evan Lee provided significant advice on the design of the study and input intoJon Choon manuscript

Dr Lake Wai provided significant advice on the design of the study and input intoChiang manuscript

Chen Yuming assisted in the statistical analysis and interpreted the dataDr Maree Ferguson provided significant advice on the design of the study, interpretation of

data and input into manuscriptProf. Lynne Daniels provided significant advice on the design of the study, interpretation of

data and input into manuscript

Principal Supervisor ConfirmationI have sighted email or other correspondence from all Co-authors confirming their certifying authorship.


sJ1&r.Sate

291









Validity and reliability of nutrition screening administered by nurses. Nutrition in Clinical Practice 2013(Accepted)


Um Su Un

~conception of the research design and planning of study, datacollection, recruitment of the participants, compilation, analysis and

Signature interpretation of the data, and writing of the manuscript5 AlAJ~Jt ;tot3

Date

Dr Emily Ang involved in the research design and commented on the manuscript

Faa Yet U assisted in the collection of data

Ng Uan Ye assisted in the collection of data

Tong Chung Yan assisted in the collection of data and input into manuscriptDr Maree Ferguson provided significant advice on the design of the study, interpretation

of data and input into manuscriptProf. Lynne Daniels provided significant advice on the design of the study, interpretation

of data and input into manuscript

Principal Supervisor ConfirmationI have sighted email or other correspondence from all Co-authors confirming their certifying authorship.


~.{(-81 n

292









Improving the performance of nutrition screening through continuous quality improvementinitiatives. Joint Commission Journal of Quality and Patient Safety 2013. (Peer-reviewed and inrevision)


Um Su Unt~ conception of the research design and planning of study, analysis andSignature interpretation of the data, and writing of the manuscript

5 (\\'\~\J~~~lJDate

Ng Sow Chun involved in the research design and commented on the manuscript

Jamie Lye assisted in writing the manuscript

Dr Loke Wai Chiong provided significant advice on the design of the study, interpretation ofdata and input into manuscript

Dr Maree Ferguson provided significant advice on the design of the study, interpretation ofdata and input into manuscript

Prof. Lynne Daniels provided significant advice on the design of the study, interpretation ofdata and input into manuscript



293









A pre-post evaluation of an ambulatory nutrition support service for malnourished patients posthospital discharge: a pilot study. Annals Academy of Medicine Singapore 2013. (In press)

Contributor Statement of contribution*Lim Su Un

~ conceptualized, designed and conducted the study,Signature interpreted the data and wrote the manuscript.

13 Ptv.&",St 2..J/3Date

Un Xianghui performed data collection and assisted in writing themanuscript

Dr Chan Yiong Huak performed statistical analysis and interpreted the data

Dr Maree Ferguson provided significant advice on the design of the study andassisted in writing the manuscript

Prof. Lynne Daniels provided significant advice on the design of the study andassisted in writing the manuscript



294

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