Cary Submits NIH/National Institute on Aging R01 PAR-17-088 Application

Kudos to Michael Cary, associate professor, and his entire team for the submission of his NIH/National Institute on Aging R01 PAR-17-088 application entitled "Successful Community Discharge Following Inpatient Rehabilitation For Older Adults." This proposal requests funding for a five-year period with a start date of Sept. 1, 2019. 

Without clear understanding of the drivers of rehospitalization and the ability to accurately predict who is at risk, we are unable to design effective interventions to reduce rehospitalizations among older adults treated in Inpatient Rehabilitation Facilities.  The purpose of this 5-year study is to develop an innovative predictive model for successful community discharge (no rehospitalization or death within 31 days following discharge from the IRF to the community) for older adults treated in Inpatient Rehabilitation Facilities.

The purpose of this study is to develop an innovative predictive model for successful community discharge for older adults treated in IRFs. Our central hypotheses are that successful community discharge and 1-year outcomes (days spent in the community, nursing home institutionalization, emergency department visits, rehospitalization, and death) for older adults will vary by specific combinations of functional limitations, geriatric syndromes, as well as differences in health service use following inpatient rehabilitation. Using 2014-2018 data from the Uniform Data System for Medical Rehabilitation and CMS (>200,000 patients within 1,112 IRFs), we propose a 5-year project with the following aims (primary outcome) and subaims (secondary outcomes): Aim 1. Identify which combinations of functional limitations (mobility, self-care, cognition) and geriatric syndromes (incontinence, pressure ulcer, depression, delirium, and falls) decrease successful community discharge (no rehospitalization or death within 31-days) following inpatient rehabilitation for older adults. We hypothesize that these combined factors will be more robust predictors than demographics or comorbidities. Subaim 1. Identify the impact of these factors on 1-year outcomes (community days, institutionalization, complications, ED visit, rehospitalization, and death). We hypothesize that mobility and self-care limitations will be more robust predictors than cognitive limitations. Multilevel analyses using linear mixed and survival models adjusting for facility-level variation will be conducted. Aim 2. Identify the impact of health services use (primary care, specialty care, outpatient rehabilitation, and home health visits) on successful community discharge following inpatient rehabilitation for older adults. We hypothesize that health services use factors will improve model accuracy. Subaim 2. Identify the impact of these factors on 1-year outcomes. We hypothesize an inverse relationship between outpatient/home health use and 1-year outcomes. Multilevel analyses using linear mixed and survival models adjusting for facility-level variation will be conducted; an innovative approach will be used to account for selection bias.