Delirium Undetected:The impact of allied health care professional documentation on delirium detection in hospitalized elders

Sheryl HodgsonCanadian Geriatrics SocietyApril 20, 2018

Disclosure

Presenter: Sheryl Hodgson

Relationships with financial sponsors: None

Disclosure of financial support

Received travel grant from McMaster University’s Geriatrics division to attend the conference

Mitigating potential bias

Not applicable

Objectives

Background

Methods

Results

Next Steps

Discussion

Delirium

APA, DSM V, 2013

Delirium

Clinical diagnosis

3 subtypes (hyperactive, hypoactive, mixed)

One of the most used, well-validated screening tools is Confusion Assessment Method Requires formal training, knowledge of

baseline

Validated as screening tool, non-diagnostic

Young et al, BMJ, 2007

Consequences of delirium

Morbidity (cognitive, physical, functional)

Mortality

Costs to healthcare system

Undiagnosed delirium One-half to two-thirds of cases

Every 48 hours spent with delirium is associated with an 11% increase in mortality.

Gonzalez et al, Psychosomatics, 2009

Why underdiagnosed?

Multiple reasons: Heterogenous clinical presentations, including fluctuation and hypoactivity

Attributed to dementia/depression No CAM/baseline assessments

Provider inexperience

Lack of awareness that delirium is marker for severe illness and mortality

Providers may still use less precise, vague words such as “confusion” or “agitation”

What’s in a chart?

One study compared charting with diagnosis of delirium by a psychiatrist using DSM-III criteria. Only 17% of the delirious patients could be recognized as delirious by rigorous

record review using ICD-9 coding terminology.

However, up to 70% if changes such as sundowning, altered mental status, lethargy recognized as indicators.

Chart-based methods more likely to identify patients with delirium behaviours overnight, and hyperactive behaviours. Even compared to regular CAM screening

Johnson et al, JAGS, 1992Saczynski et al, JAGS, 2014

What’s in a chart?

False negatives in a chart are usually due to lack of documentation

False positives more common in patients with underlying dementia

Coding data (using ICD-9 scores) less useful at excluding delirium than chart methods.

Nursing notes containing key words for delirium more common than physician notes.

Inouye et al, JAGS, 2005Puelle et al, JGN, 2015

Acting in isolation

Physicians may not see patients when exhibiting symptoms, or may not recognize symptoms if hypoactive/underlying dementia.

Potential role for allied health More frequent contact

Multiple points of contact throughout day

Overnight observation

Kales et al, JAGPN, 2003

“

”

How does allied health documentation impact delirium detection among older hospitalized inpatients

Our QI question

The concept

Quality improvement study REB waived by both Hamilton Integrated Research Ethics Board and Grand River

Hospital

Retrospective chart review from April 1, 2016 - March 31, 2017 Random sample of cohort

203 geriatric patients admitted to medicine beds in a non-academic community hospital in southwestern Ontario 13% of admissions in this cohort

≧70 years old

Excluded if: <70, stroke, subsequent admission, ICU patients

Intervention

Delirium identified by chart review vs data sent to CIHI Physician and Allied Health documentation

Sample Size Calculation Estimated detection of 30% incidence of delirium with physician charting

Additional 10% based on allied health care documentation Estimated total rate of 40%

With a power calculation of 80% and a Type 1 error rate of 5% a sample size of 353 charts is required

Pre-analysis planned after 150 charts to assess for early statistical differences With findings, maintained power and error rate with sample of 185 charts

Methods “Delirium” in chart

Or trigger word: Altered mental status

Disorient/disoriented

Reorient

Encephalopathy

Hallucination

Confusion

Trigger words validated by 2015 chart abstraction study in Journal of Gerontological Nursing

Puelle et al, JGN, 2015

Methods Characteristic ValueAge (years)Average +/‐ SD 81.48 +/‐ 7.29

Median 82

GenderFemale, n (%) 109 (58)

Male, n (%) 79 (42)

Admitted fromHome, n (%) 133 (70.7)

Retirement Home, n (%) 32 (17)

Long‐Term Care, n (%) 12 (6.3)

Other/Unidentified, n (%) 11 (5.8)

WardACE, n (%) 15 (8)

CTU, n (%) 46 (24.4)

Medicine bed, n (%) 118 (62.7)

Other, n (%) 9 (4.7)

Length of Stay (days)Average +/‐ SD 6.04 +/‐ 5.26 

1500 patients in

cohort

203 Charts

15 Excluded

• Stroke (6)• Admitted

post-deadline (8)

• Died in ER (1)

188Reviewed

• Power re-calculated.

• Satisfactory based on findings

Random sample

Patient characteristics (n=188)

Protocol Pilot done with 10 charts to

assess abstractor agreement prior to review

Kappa 1.0 proceeded

10% of charts reviewed independently in duplicate

100% agreement

Detection of delirium

Total (%) MD (%) Allied (%)

Delirious 107 (57%) 68 (36%) 39 (21%)

Non-Delirious 81 (43%) 120 (64%)

n/a

Delirious by physician

Non-delirious

Delirious by allied health

Allied health breakdown

Of allied health care worker documentation Nurse: All 39

Others: OT/PT, HELP program volunteer and Spiritual Care.

Pharmacy charts could not be accessed

Nurse charting identified all cases of delirium

Minor association with actual CAM score (3 CAM +ve)

Discussion

Allied health care professional documentation may increase the detection of delirium In our study, 37% beyond physician charting

Our study suggests the most important allied health care workers for increasing detection are nurses They have the most contact with patients out of any care provider

Do the most frequent charting

Limitations

Use of confusion as a trigger word is a confounder. Not able to detect the difference between delirium and baseline dementia In addition, initially validated in population of surgical patients without previous

diagnosis of dementia

Did not compare allied health charting with physicians – assessing for additive value, not congruence

Retrospective

No formal screening for delirium to compare results to

Single centre. Results may not apply elsewhere.

Why are the findings important?

Provides a greater understanding of how allied health professionals can potentially improve the care of older patients in hospital

Suggest we can increase detection of delirium within existing multidisciplinary team habits and structures

1. Impact on patients1. Increasing detection of delirium and earlier detection of delirium may lead to reduced

morbidity/mortality

2. Impact on care team1. Identifies area where enhanced communication beneficial

3. Impact on hospital1. May result in increased funding

2. Helps direct QI initiatives

Next Steps

Hospital formalization of allied role in delirium detection Multidisciplinary care and assessment is key

This may be facilitated by pre-existing Electronic Health Records

No paper abstracting needing

Physician and allied health care training Look into initiatives to increase awareness

Teach caregivers to read notes from other team members

Discuss coding policies with Canadian Institutes of Health Information (CIHI) Consider a method that includes allied health care documentation

References American Psychiatric Association. DSM-V.; 2013. doi:10.1176/appi.books.9780890425596.744053.

Fick DM, Steis MR, et al. Delirium superimposed on dementia is associated with prolonged length of stay and poor outcomes in hospitalized older adults. J Hosp Med. 2013;8(9):500-505. doi:10.1002/jhm.2077.

González M, Martínez G, et al. Impact of delirium on short-term mortality in elderly inpatients: a prospective cohort study. Psychosomatics. 2009;50(3):234-238. doi:10.1176/appi.psy.50.3.234.

Inouye SK, Leo-summers ÃL, et al. A Chart-Based Method for Identification of Delirium : Validation Assessment Method. J Am Geriatr Soc. 2005;53(2):312-318.

Johnson JC, Kerse NM, et al. Prospective versus Retrospective Methods of Identifying Patients with Delirium. J Am Geriatr Soc. 1992;40(4):316-319. doi:10.1111/j.1532-5415.1992.tb02128.x.

Kales HC, Kamholz BA, et al. Recorded Delirium in a National Sample of Elderly Inpatients: Potential Implications for Recognition. J Geriatr Psychiatry Neurol. 2003;16(1):32-38. doi:10.1177/0891988702250535.

Puelle MR, Kosar CM, et al. from Medical Records. 2016;41(8):34-42. doi:10.3928/00989134-20150723-01.

Saczynski JS, Kosar CM, et al. A tale of two methods: Chart and interview methods for identifying delirium. J Am Geriatr Soc. 2014;62(3):518-524. doi:10.1111/jgs.12684.

Young J, Inouye SK. Delirium in older people. Br Med J. 2007;334(7598):842-846. doi:10.1136/bmj.39169.706574.AD.

Wei LA, Fearing MA, et al. The Confusion Assessment Method (CAM): A Systematic Review of Current Usage. Int J. 2008;56(5):823-830. doi:10.1111/j.1532-5415.2008.01674.x.

Acknowledgements

Dr. Joanne Ho, GeriMedRisk, Schlegel Research Institute for the Ageing, McMaster University

Dr. Jennifer Tung, GeriMedRisk, Grand River Hospital

Dr. Saurabh Kalra, McMaster University

Chantelle Archer, Grand River Hospital

Lindsay Cox, GeriMedRisk

Tara McGlynn, Grand River Hospital

Nael Abumustafa, Grand River Hospital

Questions?