Wan Thomas T H, Ortiz Judith, Du Alice, Golden Adam G
College of Health and Public Affairs, University of Central Florida, P.O.Box 163680, Orlando, FL, 32816-3680, USA.
Orlando Veterans Affairs Medical Center, Orlando, FL, 32827, USA.
Health Care Manag Sci. 2017 Mar;20(1):94-104. doi: 10.1007/s10729-015-9339-x. Epub 2015 Sep 15.
The enactment of the Patient Protection and Affordable Care Act (ACA) has been expected to improve the coverage of health insurance, particularly as related to the coordination of seamless care and the continuity of elder care among Medicare beneficiaries. The analysis of longitudinal data (2007 through 2013) in rural areas offers a unique opportunity to examine trends and patterns of rural disparities in hospital readmissions within 30 days of discharge among Medicare beneficiaries served by rural health clinics (RHCs) in the eight southeastern states of the Department of Health & Human Services (DHHS) Region 4. The purpose of this study is twofold: first, to examine rural trends and patterns of hospital readmission rates by state and year (before and after the ACA enactment); and second, to investigate how contextual (county characteristic), organizational (clinic characteristic) and ecological (aggregate patient characteristic) factors may influence the variations in repeat hospitalizations. The unit of analysis is the RHC. We used administrative data compiled from multiple sources for the Centers of Medicare and Medicaid Services for a period of seven years. From 2007 to 2008, risk-adjusted readmission rates increased slightly among Medicare beneficiaries served by RHCs. However, the rate declined in 2009 through 2013. A generalized estimating equation of sixteen predictors was analyzed for the variability in risk-adjusted readmission rates. Nine predictors were statistically associated with the variability in risk-adjusted readmission rates of the RHCs pooled from 2007 through 2013 together. The declined rates were associated with by the ACA effect, Georgia, North Carolina, South Carolina, and the percentage of elderly population in a county where RHC is located. However, the increase of risk-adjusted rates was associated with the percentage of African Americans in a county, the percentage of dually eligible patients, the average age of patients, and the average clinical visits by African American patients. The sixteen predictors accounted for 21.52 % of the total variability in readmissions. This study contributes to the literature in health disparities research from the contextual, organizational and ecological perspectives in the analysis of longitudinal data. The synergism of multiple contextual, organizational and ecological factors, as shown in this study, should be considered in the design and implementation of intervention studies to address the problem of hospital readmissions through prevention and enhancement of disease management of rural Medicare beneficiaries.
《患者保护与平价医疗法案》（ACA）的颁布有望提高医疗保险覆盖率，特别是在无缝医疗协调以及医疗保险受益人中老年人护理连续性方面。对农村地区纵向数据（2007年至2013年）的分析提供了一个独特的机会，可用于研究美国卫生与公众服务部（DHHS）第4地区八个东南部州农村健康诊所（RHC）服务的医疗保险受益人出院后30天内医院再入院情况的农村差异趋势和模式。本研究的目的有两个：第一，按州和年份（ACA颁布前后）研究农村医院再入院率的趋势和模式；第二，调查背景（县特征）、组织（诊所特征）和生态（总体患者特征）因素如何可能影响再次住院的差异。分析单位是农村健康诊所。我们使用了从医疗保险和医疗补助服务中心多个来源汇编的七年行政数据。2007年至2008年，农村健康诊所服务的医疗保险受益人中风险调整后的再入院率略有上升。然而，2009年至2013年该比率下降。对16个预测因素的广义估计方程进行了分析，以研究风险调整后再入院率的变异性。9个预测因素与2007年至2013年汇总的农村健康诊所风险调整后再入院率的变异性在统计学上相关。下降的比率与ACA效应、佐治亚州、北卡罗来纳州、南卡罗来纳州以及农村健康诊所所在县的老年人口百分比有关。然而，风险调整率的上升与县内非裔美国人的百分比、双重资格患者的百分比、患者的平均年龄以及非裔美国患者的平均临床就诊次数有关。这16个预测因素占再入院总变异性的21.52%。本研究从纵向数据分析的背景、组织和生态角度为健康差异研究文献做出了贡献。如本研究所示，在设计和实施干预研究以通过预防和加强农村医疗保险受益人的疾病管理来解决医院再入院问题时，应考虑多个背景、组织和生态因素的协同作用。
