美国县级房屋改造使用的预测因素。

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
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引用次数: 0

摘要

背景:地理空间分析表明,美国退伍军人事务部(VA)规定的房屋改造(HM)服务并没有在美国统一使用。方法:本研究的目的是确定与HISA使用率相关的县特征,如县级临床护理和护理质量指标、与自然环境相关的变量和社会人口特征。采用多元回归分析从县级变量对县级资源利用率进行预测。结果:县级HISA使用率高度倾斜,范围为0.09 ~ 59.7%,平均为6.6%,中位数为5%。未参保成年人百分比和可预防住院率成为县级HISA使用率的重要预测因子。未参保成人比例与HISA使用率呈负相关(b = -8.99, P = 0.005)。成人未参保比例越高,HISA使用率越低。县级可预防住院率与县级HISA使用率呈正相关(b = .0004, P = .009)。县级住房质量预测因子与县级HISA使用率无显著相关。结论:本研究填补了有关县域变量影响和HISA地理分布及使用的文献空白。需要更多的研究来了解和解释HISA使用的地理差异。这项工作是在广泛水平上量化和预测HISA利用率的第一步,目标是增加残疾退伍军人获得HISA的机会。
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Predictors of County-Level Home Modification Use Across the US.

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.

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