Wan Thomas T H, Lin Yi-Ling, Ortiz Judith
College of Health and Public Affairs, Doctoral Program in Public Affairs, University of Central Florida, Orlando, FL.
College of Health and Public Affairs, University of Central Florida, Orlando, FL, Address: P.O. Box 162369, Orlando, FL 32816,
Res Sociol Health Care. 2016;34:135-152. doi: 10.1108/S0275-495920160000034008.
The purpose of this study is to examine what factors contributing to the variability in chronic obstructive pulmonary disorder (COPD) and asthma hospitalization rates when the influence of patient characteristics is being simultaneously considered by applying a risk adjustment method. A longitudinal analysis of COPD and asthma hospitalization of rural Medicare beneficiaries in 427 rural health clinics (RHCs) was conducted utilizing administrative data and inpatient and outpatient claims from Region 4. The repeated measures of risk-adjusted COPD and asthma admission rate were analyzed by growth curve modeling. A generalized estimating equation (GEE) method was used to identify the relevance of selected predictors in accounting for the variability in risk-adjusted admission rates for COPD and asthma. Both adjusted and unadjusted rates of COPD admission showed a slight decline from 2010 to 2013. The growth curve modeling showed the annual rates of change were gradually accentuated through time. GEE revealed that a moderate amount of variance (marginal R = 0.66) in the risk-adjusted hospital admission rates for COPD and asthma was accounted for by contextual, ecological, and organizational variables. The contextual, ecological, and organizational factors are those associated with RHCs, not hospitals. We cannot infer how the variability in hospital practices in RHC service areas may have contributed to the disparities in admissions. Identification of RHCs with substantially higher rates than an average rate can portray the need for further enhancement of needed ambulatory or primary care services for the specific groups of RHCs. Because the risk-adjusted rates of hospitalization do not very by classification of rural area, future research should address the variation in a specific COPD and asthma condition of RHC patients. Risk-adjusted admission rates for COPD and asthma are influenced by the synergism of multiple contextual, ecological, and organizational factors instead of a single factor.
本研究的目的是通过应用风险调整方法，在同时考虑患者特征影响的情况下，探究导致慢性阻塞性肺疾病（COPD）和哮喘住院率变异性的因素。利用来自第4地区的行政数据以及住院和门诊理赔数据，对427家农村健康诊所（RHC）中农村医疗保险受益人的COPD和哮喘住院情况进行了纵向分析。通过生长曲线模型分析了风险调整后的COPD和哮喘入院率的重复测量值。采用广义估计方程（GEE）方法来确定所选预测因素在解释COPD和哮喘风险调整后入院率变异性方面的相关性。2010年至2013年期间，COPD调整后和未调整后的入院率均略有下降。生长曲线模型显示，年变化率随时间逐渐加剧。GEE显示，COPD和哮喘风险调整后住院率的适度方差（边际R = 0.66）可由背景、生态和组织变量来解释。背景、生态和组织因素是与RHC相关的因素，而非医院。我们无法推断RHC服务区域内医院实践的变异性可能如何导致了入院差异。识别出入院率远高于平均水平的RHC，可以表明有必要进一步加强针对特定RHC群体的门诊或初级保健服务。由于风险调整后的住院率不会因农村地区分类而有很大差异，未来的研究应关注RHC患者特定COPD和哮喘病情的变异性。COPD和哮喘的风险调整后入院率受多种背景、生态和组织因素协同作用的影响，而非单一因素。
