Lee A J, Huber J H, Stason W B
Health Economics Research, Inc., Waltham, MA 02154, USA.
Health Serv Res. 1997 Jun;32(2):197-221; discussion 223-7.
To analyze geographic variability in the utilization and cost of post-stroke medical care using multiple linear regression.
DATA SOURCES/STUDY SETTING: A 20 percent random sample of Medicare beneficiaries with an admission to an acute care hospital for stroke during the first six months of 1991, supplemented by data from their Medicare claims and beneficiary records, the Medicare Cost Reports for hospitals and nursing homes, and the Area Resource File.
Weighted least squares regression is used to analyze variations in post-stroke practice patterns across 151 MSAs (Metropolitan Statistical Areas). Average post-stroke costs, utilization rates, and facility lengths of stay are regressed on patient and market characteristics.
DATA COLLECTION/EXTRACTION METHODS: For a six-month post-stroke interval, beneficiary-level post-stroke costs and service utilization are averaged by MSA. Variables describing market conditions are then added to these MSA-level records.
Patient variables rarely explain more than a third of practice variation, and often they explain substantially less than that. Market variables (with some exception) tend to be relatively less important. Finally, one-half to two-thirds of the practice variation across MSAs is unexplained by the patient and market factors measured in our data.
A substantial portion of inter-MSA variability in utilization and intensity of post-stroke rehabilitation services cannot be explained by differences in patient characteristics. Given the large practice differences observed across MSAs, it seems unlikely that unmeasured patient differences can account for much more of the practice differences.
运用多元线性回归分析中风后医疗护理的使用情况及成本的地域差异。
数据来源/研究背景:1991年上半年因中风入住急症医院的医疗保险受益人的20%随机样本,并辅以他们的医疗保险理赔和受益人记录数据、医院和疗养院的医疗保险成本报告以及区域资源文件。
加权最小二乘法回归用于分析151个大都市统计区(MSA)中风后医疗模式的差异。中风后的平均成本、使用率和住院设施时长以患者和市场特征为自变量进行回归分析。
数据收集/提取方法:在中风后的六个月期间,按大都市统计区对受益人的中风后成本和服务使用情况进行平均。然后将描述市场状况的变量添加到这些大都市统计区层面的记录中。
患者变量很少能解释超过三分之一的医疗模式差异,而且通常解释程度远低于此。市场变量(有一些例外情况)往往相对不太重要。最后,我们数据中所衡量的患者和市场因素无法解释大都市统计区之间二分之一至三分之二的医疗模式差异。
中风后康复服务的使用情况和强度在大都市统计区之间的显著差异无法通过患者特征的差异来解释。鉴于在各都市统计区观察到的巨大医疗模式差异,未测量的患者差异似乎不太可能解释更多的医疗模式差异。