Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Med Care. 2010 Feb;48(2):175-82. doi: 10.1097/MLR.0b013e3181c16102.
The objective of this study was to evaluate an administrative data-based risk adjustment method for predicting physician utilization and the contribution of survey-derived indicators of health status. The results of this study will support the use of administrative data for planning, reimbursement, and assessing equity of physician utilization.
The Ontario portion of the 2000-2001 Canadian Community Health Survey was linked with administrative physician claims data from 2002-2003 and 2003-2004. Explanatory models of family physician (FP) and specialist physician (SP) utilization were run using demographic information and The Johns Hopkins University Adjusted Clinical Groups (ACG) Case-mix System. Survey-based measures of health status were then added to the models. The coefficient of determination, R, indicated the models' explanatory power.
The study sample consisted of 25,558 individuals aged 20 to 79 years representing approximately 7.8 million people. Over the 2 years of study period, 82.5% of the study population had a FP visit with a median of 6 visits and 53.2% had a SP visit with a median of 1 visit. The R values based on administrative data alone were 33% and 21% for the frequency of FP and SP visits and 16% and 35% for having one or more visit to an FPs and SPs, respectively. The addition of the survey-based measures to the administrative data-based models produced less than a 2% increase in explanatory power for any outcome.
Administrative data-based measures of morbidity burden are valid and useful indicators of future physician utilization. The survey-derived measures used in this study did not contribute significantly to models on the basis of administrative data-based measures. These findings support the future use of administrative data-based data and Adjusted Clinical Groups for planning, reimbursement, and research.
本研究旨在评估一种基于管理数据的风险调整方法，以预测医生的使用情况，并评估健康状况的调查指标的贡献。本研究的结果将支持使用管理数据进行规划、报销和评估医生使用的公平性。
将 2000-2001 年加拿大社区健康调查的安大略省部分与 2002-2003 年和 2003-2004 年的管理医生索赔数据进行了链接。使用人口统计学信息和约翰霍普金斯大学调整临床组（ACG）病例组合系统对家庭医生（FP）和专科医生（SP）使用的解释模型进行了运行。然后将基于调查的健康状况指标添加到模型中。决定系数 R 表示模型的解释能力。
研究样本包括 25558 名年龄在 20 至 79 岁之间的个体，代表约 780 万人。在研究期间的 2 年中，82.5%的研究人群有 FP 就诊，中位数为 6 次就诊，53.2%有 SP 就诊，中位数为 1 次就诊。仅基于管理数据的 R 值分别为 FP 和 SP 就诊频率的 33%和 21%，以及分别有 1 次或更多次就诊的 FP 和 SP 的 16%和 35%。将基于调查的措施添加到基于管理数据的模型中，对任何结果的解释能力增加不到 2%。
基于管理数据的发病率负担指标是未来医生使用情况的有效和有用的指标。本研究中使用的基于调查的指标对基于管理数据的指标的模型贡献不大。这些发现支持未来使用基于管理数据的 Adjusted Clinical Groups 进行规划、报销和研究。
