Using Quality Indicator Codes to Identify Patients' Fall Risk in Inpatient Rehabilitation Facilities.

Wright, Jonathan R; D'Ausilio, Jamie; Holmberg, Janene M; Timpson, Misti; Preston, Trevor; Woodfield, Devyn; Snow, Gregory L · Arch Phys Med Rehabil · 2023

retrospective_cohort · Level III

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Abstract

To discover if quality indicator (QI) codes are associated with patient falls in inpatient rehabilitation facilities (IRFs). This retrospective cohort study explored differences between patients who fell and those who did not fall. We analyzed potential associations between QI codes and falls using univariable and multivariable logistic regression models. We collected data from electronic medical records at 4 IRFs. In 2020, our 4 data collection sites admitted and discharged a total of 1742 patients older than 14 years . We only excluded patients (N=43) from statistical analysis if they were discharged before admission data had been assigned. Not applicable. Using a data extraction report, we collected age, sex, race and ethnicity, diagnosis, falls, and QI codes for communication, self-care, and mobility performance. Staff documented communication codes on a 1-4 scale and self-care and mobility codes on a 1-6 scale, with higher codes representing greater independence. Ninety-seven patients (5.71%) fell in the 4 IRFs over a 12-month period. The group who fell had lower QI codes for communication, self-care, and mobility. When adjusting for bed mobility, transfer, and stair-climbing ability, low performance with understanding, walking 10 feet, and toileting were significantly associated with falls. Patients with admission QI codes below 4 for understanding had 78% higher odds of falling. If they were assigned admission QI codes below 3 for walking 10 feet or toileting, they had 2 times greater odds of falling. We did not find a significant association between falls and patients' diagnosis, age, sex, or race and ethnicity in our sample. Communication, self-care, and mobility QI codes appear to be significantly associated with falls. Future research should explore how to use these required codes to better identify patients likely to fall in IRFs.

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