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2015 HSR&D/QUERI National Conference Abstract

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3011 — Identifying Risk Factors for Wheelchair Falls and Injuries in Elderly Veterans

Spehar AM, COIN-North Florida/South Georgia and Tampa; VISN 8 Patient Safety Center of Inquiry; Mbah AK, COIN-North Florida/South Georgia and Tampa; VISN 8 Patient Safety Center of Inquiry; Patel NR, COIN-North Florida/South Georgia and Tampa; Byrd RA, VISN 8 Patient Safety Center of Inquiry; Friedman Y, VISN 8 Patient Safety Center of Inquiry; Bulat T, VISN 8 Patient Safety Center of Inquiry;

Objectives:
To develop a risk assessment model for elderly Veterans in wheelchairs that identifies risk factors for falls and fall-related injuries.

Methods:
Self-reported data on wheelchair falls and injuries were collected at baseline and monthly (via telephone calls) from Veterans (N = 741) who routinely used a wheelchair for mobility. Data collected included characteristics of: wheelchair users, wheelchairs, wheelchair activities and skills, physical environment, falls, and injuries. Descriptive statistics included chi-squared test for categorical variables and t-test (2-sided) for continuous variables. Logistic regression models using a backward elimination approach and Poisson regression models were employed to select the best predictors of falls and injuries.

Results:
Risk factors for wheelchair-related falls included: fair/poor health status (p = 0.016), pain interference with activities (p = 0.021), pain in transfer (p = 0.001), low energy levels (p = 0.005), and needing car lift (p = 0.0239) or reaching device (p = 0.0119). Modeling by logistic regression and Poisson regression methods verified these to be the best predictors of falls. Risk factors for injuries mirrored these findings. Additional analyses may identify other factors that increase the risk for falls and injuries in elderly Veterans using a wheelchair for mobility.

Implications:
We identified several risk factors for falls and injuries in elderly Veterans who routinely used a wheelchair for mobility. Many of the risk factors are different from those identified in ambulatory populations, are strongly predictive, and can readily be obtained via a simple questionnaire.

Impacts:
Identification of risk factors for falls and injuries in this vulnerable population of elderly Veterans permits implementation of educational, therapeutic and other safety measures tailored to this cohort.