Luz M Semeah, Tatiana Orozco, Xinping Wang, Huanguang Jia, Mi Jung Lee, Lauren K Wilson, Shanti P Ganesh, Zaccheus J Ahonle, Deepthi Satheesa Varma, Eric R Litt, Justin Kilkenny Ahern, Leslie M Santos Roman, Diane C Cowper Ripley
{"title":"Predictors of County-Level Home Modification Use Across the US.","authors":"Luz M Semeah, Tatiana Orozco, Xinping Wang, Huanguang Jia, Mi Jung Lee, Lauren K Wilson, Shanti P Ganesh, Zaccheus J Ahonle, Deepthi Satheesa Varma, Eric R Litt, Justin Kilkenny Ahern, Leslie M Santos Roman, Diane C Cowper Ripley","doi":"10.12788/fp.0279","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Geospatial analyses illustrating where the Home Improvements and Structural Alterations program (HISA) have been prescribed suggest that home modification (HM) services under US Department of Veterans Affairs (VA) is not prescribed and used uniformly across the US.</p><p><strong>Methods: </strong>The objective of this study was to identify county characteristics associated with HISA use rates, such as county-level measures of clinical care and quality of care, variables related to physical environment, and sociodemographic characteristics. Multiple regression analysis was used to predict county-level utilization rate from county-level variables.</p><p><strong>Results: </strong>County-level HISA use was highly skewed and ranged from 0.09 to 59.7%, with a mean of 6.6% and median of 5%. Percent uninsured adults and rate of preventable hospital stays emerged as significant predictors of county-level HISA utilization rate. Specifically, county percentage of uninsured adults was negatively related to county-level HISA utilization rate (<i>b</i> = -8.99, <i>P</i> = .005). The higher the proportion of uninsured adults the lower the HISA utilization rate. The county rate of preventable hospital stays was positively related to county-level HISA utilization rate (<i>b</i> = .0004, <i>P</i> = .009). County-level predictors of housing quality were not significantly associated with county-level HISA utilization rate.</p><p><strong>Conclusions: </strong>Our research fills a gap in the literature about the impact of county-level variables and the geographic distribution and use of HISA. More research is needed to understand and account for geographical variation in HISA use. This work serves as a first step at quantifying and predicting HISA utilization rate at a broad level, with the goal of increasing access to HMs for veterans with disabilities.</p>","PeriodicalId":73021,"journal":{"name":"Federal practitioner : for the health care professionals of the VA, DoD, and PHS","volume":"39 6","pages":"274-280"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648602/pdf/fp-39-06-274.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Federal practitioner : for the health care professionals of the VA, DoD, and PHS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12788/fp.0279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/6/16 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Geospatial analyses illustrating where the Home Improvements and Structural Alterations program (HISA) have been prescribed suggest that home modification (HM) services under US Department of Veterans Affairs (VA) is not prescribed and used uniformly across the US.
Methods: The objective of this study was to identify county characteristics associated with HISA use rates, such as county-level measures of clinical care and quality of care, variables related to physical environment, and sociodemographic characteristics. Multiple regression analysis was used to predict county-level utilization rate from county-level variables.
Results: County-level HISA use was highly skewed and ranged from 0.09 to 59.7%, with a mean of 6.6% and median of 5%. Percent uninsured adults and rate of preventable hospital stays emerged as significant predictors of county-level HISA utilization rate. Specifically, county percentage of uninsured adults was negatively related to county-level HISA utilization rate (b = -8.99, P = .005). The higher the proportion of uninsured adults the lower the HISA utilization rate. The county rate of preventable hospital stays was positively related to county-level HISA utilization rate (b = .0004, P = .009). County-level predictors of housing quality were not significantly associated with county-level HISA utilization rate.
Conclusions: Our research fills a gap in the literature about the impact of county-level variables and the geographic distribution and use of HISA. More research is needed to understand and account for geographical variation in HISA use. This work serves as a first step at quantifying and predicting HISA utilization rate at a broad level, with the goal of increasing access to HMs for veterans with disabilities.