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Same Level Falls and TBIs in Older Adults: The Research

Journey

Linda J. Scheetz, EdD, RN, FAENLehman College and the Graduate CenterCity University of New York, NY, USA

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Acknowledgement

This study was funded by a grant from Lehman College, City University of New York

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My Research Journey

• Early studies evaluated undertriage of older injured adults

• NJ hospital discharge data• Results– NJ counties with TCs• 18% older men undertriaged• 15% older women undertriaged

– NJ statewide• 40% older men and women undertriaged

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My Research Journey

• National study of undertriage of MVC patients comparing undertriage before and after ACS field triage guidelines changed in 2006

• NASS CDS study of patients 55 years and older• Results– 2004: 42% undertriaged– 2008: 22% undertriaged

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My Research Journey

• 2010 study compared AIS 3, 4, 5 injuries in patients 65 years and older who were correctly triaged with those who were undertriaged

• NASS CDS data (motor vehicle injuries)• Brain injuries were the most commonly

undertriaged injury (31.1% of all injuries)

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Background for Today’s Study

• All cause trauma incidence is lower for older adults compared to young and middle-aged adults (NTDB, 2014)

• All cause case fatality rates are highest among older adults (NTDB, 2014)

• Falls and MVCs account for most trauma incidents in older adults (NTDB, 2014)

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Background

• Falls are the leading cause of fatal (54.1%)and nonfatal (62.5%) injuries among older adults, (CDC, 2012)

• 1 in 3 people age 65 and older falls each year (CDC, 2012)

• 20-30% sustain moderate to severe injuries that decrease their functional ability (CDC, 2012)

• At all ISS levels, fatality rates are higher for older adults (NTDB, 2014)

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Background

unspecified same level steps & stairs bed wheelchair other0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

All Causes of Fatal Falls, 2012

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Background

• Falls are the most common cause of TBIs among older adults (CDC, 2014)

• The number of TBIs among older adults has increased sharply in the past decade (CDC, 2014)

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TBI Incidence from Falls

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Study PurposeThis study examined the epidemiology of fall

injuries among older adults who sustained TBIs from same level falls

Specific aims:• Identify incidence and type of TBIs• Identify additional injuries• Identify predictors of LOS, mortality, TC

admission

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Significance

• Same level falls are low energy injuries• The potential for serious injury may be

overlooked by bystanders, EMS responders and ED staff

• The potential for serious, life-threatening injuries must be considered

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Methods

• Sample– Records extracted from the Healthcare Cost &

Utilization Project N.Y. State Inpatient Database (HCUP SID), Agency for Healthcare Research and Quality

– Inclusion criteria• Age 65 years and older• Primary E-code of same level fall • Primary diagnosis of traumatic brain injury

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Outcome Variables

• Short-term mortality • Hospital length of stay• Trauma center admission

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Predictor Variables

• Sociodemographic • TBI severity• Number of diagnoses• Chronic diseases• Primary and secondary payers• Patient residency location (urban, rural, etc.)• Major surgery (LOS model)• LOS (mortality LR model)• TC admission (mortality model)

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Data Analysis• PASW (SPSS) Statistics 18• Descriptive analysis of sample• Chi square analysis – Fall mechanism and type of TBI – Fall mechanism and injury outcomes

• Logistic regression to identify predictors of:– LOS– Short-term mortality– TC admission

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Incidence• 57,196 patients with primary injury

mechanism of fall • 20,876 patients who experienced same level

fall (36.5%)• 3,331 patients with same level fall and TBI– 5.82 % of all patients who fell and were

hospitalized– 16.0% of all patients who had same level fall and

were hospitalized

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Results – Sample Description

• 3,331 patients admitted for TBI (same level fall)• 52.6% (n=1752) were female• Mean age = 81.1 years (SD = 8.1) • Median LOS = 5 days• Mean number of chronic conditions = 4.5 (SD

2.2)• 347 persons (10.4%) died

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Results: Additional Injuries

• Hundreds of additional injuries– Additional TBIs (diagnoses 2-15)– Fractures of the facial bones, upper and lower

extremities, hip, pelvis, vertebral column (with and without SCI), ribs, and sternum

– Strains, sprains, contusions with skin intact– Open wounds– Hemothorax, pneumothorax

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Predictors of Mortality

• To select variables for the logistic regression model, all sociodemographic, clinical and comorbidity variables were individually evaluated for their significance in predicting mortality

• Variables that individually predicted mortality (p=/<.05) were added to the LR model

• Model fit was verified

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Results: Predictors of Mortality Predictors O.R. Interpretation C.I.

Lymphoma 2.788 279% more likely to die 1.233 - 6.304

Brain injury severity

2.608 261% more likely to die 1.602 - 4.245

Weight loss 2.483 248% more likely to die 1.491 - 4.137

Metastatic cancer 2.336 234% more likely to die 1.222 - 4.468

Solid tumor cancer

2.114 211% more likely to die 1.131 - 3.953

Coagulation disorder

1.993 Twice as likely to die 1.321- 3.009

CHF 1.552 55% more likely to die 1.134-2.124

TC admission 1.488 49% more likely to die 1.174-1.885

Age 1.032 3% more likely to die 1.016-1.047

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Predictors of LOS

• To select variables for the logistic regression model, all sociodemographic, clinical and comorbidity variables were individually evaluated for their significance in predicting LOS

• Variables that individually predicted LOS (p=/<.05) were added to the LR model

• Model fit was verified

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Results: Predictors of LOSPredictors O.R. Interpretation C.I.

Race, Black*major surgery

9.090 Nine times more likely longer LOS

4.604 - 17.949

Major surgery 5.807 Nearly 6 times more likely longer LOS

4.673 - 7.216

Race, Black 2.066 Twice as likely longer LOS 1.504 - 2.837

Race, Other, mixed

1.590 59%% more likely longer LOS 1.100 - 2.297

Number diagnoses

1.369 Each additional diagnosis, 37% more likely longer LOS

1.320 - 1.420

Age 1.012 Each year older, 1% more likely longer LOS

1.002 - 1.022

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Predictors of TC Admission

• To select variables for the logistic regression model, all sociodemographic, clinical and comorbidity variables were individually evaluated for their significance in predicting TC admission

• Variables that individually predicted TC admission (p=/<.05) were added to the LR model

• Model fit was verified

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Results: Predictors of TC AdmissionPredictors O.R. Interpretation C.I.

Medicaid 5.803 Nearly 6 times as likely 1.555 - 21.659Wealthiest quartile 3.913 Nearly 4 times as likely 3.072 - 4.985

Other insurance 2.782 Nearly 3 times as likely 1.439 - 5.381

2nd wealthiest quartile 2.205 More than twice as likely 1.730 - 2.810

Race, mixed 1.909 Nearly twice as likely 1.274 - 2.860Location, 10-50k pop 1.763 76% more likely 1.230 - 2.527

Hispanic ethnicity 1.601 60% more likely 1.149 - 2.232Age, 75-84 1.582 58% more likely 1.074 - 1.5182nd poorest quartile 1.566 57% more likely 1.226 - 1.998

Age, 65-74 1.278 28% more likely 1.033 - 1.582Number diagnoses 1.045 5% more likely each diag 1.012 - 1.079Private insurance 1.478 Nearly 50% more likely 1.014 - 2.153

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Discussion

• Brain atrophy and other neuro changes predispose older persons to TBI

• Prehospital identification of TBIs difficult – 48 % transported to NTCs

• Age and chronic diseases contribute to frailty• Mortality and LOS increase as age increases• TC admits decrease as age increases• Further investigation needed re:

sociodemographic factors

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Implications for ED Nurses• Maintain high index of suspicion for TBI• Detailed history on all older fall patients• Serial neurological assessments• Appropriate diagnostic workup• Monitor effectiveness of ED triage protocols• Consider developing protocol for evaluation and

treatment of older fall patients• Clear and written discharge instructions, verify

understanding

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The Journey Continues

• My current study examines time to deterioration of the GCS– Study collaborators are Michael Horst and Richard

Arbour– We are about to begin data analysis!

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References

• Centers for Disease Control and Prevention, Falls Among Older Adults: An Overview, 2013. Retrieved from: http://www.cdc.gov/HomeandRecreationalSafety/Falls/adultfalls.html

• Centers for Disease Control and Prevention, WISQARS. Retrieved from: http://www.cdc.gov/injury/wisqars/index.html

• American College of Surgeons, National Trauma Data Bank Report. Retrieved from: https://www.facs.org/~/media/files/quality%20programs/trauma/ntdb/ntdb%20annual%20report%202014.ashx

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References

• World Health Organization, WHO Global Report on Falls Prevention in Older Age, 2007. Available: http://www.who.int/ageing/publications/Falls_prevention7March.pdf

• Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases, Agency for Healthcare Research and Quality (AHRQ), 2013. Available: http://www.hcup-us.ahrq.gov/sidoverview.jsp