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Comparing the agreement among alternative models in evaluating HMO efficiency.

机译:比较替代模型之间在评估HMO效率方面的一致性。

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摘要

OBJECTIVE: To describe the efficiency of HMOs and to test the robustness of these findings across alternative models of efficiency. This study examines whether these models, when constructed in parallel to use the same information, provide researchers with the same insights and identify the same trends. DATA SOURCES: A data set containing 585 HMOs operating from 1985 through 1994. Variables include enrollment, utilization, and financial information compiled primarily from Health Care Investment Analysts, InterStudy HMO Census, and Group Health Association of America. STUDY DESIGN: We compute three estimates of efficiency for each HMO and compare the results in terms of individual performance and industry-wide trends. The estimates are then regressed against measures of case mix, quality, and other factors that may be related to the model estimates. PRINCIPAL FINDINGS: The three models identify similar trends for the HMO industry as a whole; however, they assess the relative technical efficiency of individual firms differently. Thus, these techniques are limited for either benchmarking or setting rates because the firms identified as efficient may be a consequence of model selection rather than actual performance. CONCLUSIONS: The estimation technique to evaluate efficient firms can affect the findings themselves. The implications are relevant not only for HMOs, but for efficiency analyses in general. Concurrence among techniques is no guarantee of accuracy, but it is reassuring; conversely, radically distinct inferences across models can be a warning to temper research conclusions.
机译:目的:描述HMO的效率,并在其他效率模型中测试这些发现的稳健性。这项研究检验了这些模型是否可以并行构建以使用相同的信息,从而为研究人员提供相同的见解并确定相同的趋势。数据来源:该数据集包含1985年至1994年运营的585个HMO。变量包括入学,使用和财务信息,这些信息主要是从Health Care Investment Analysts,InterStudy HMO Census和美国Group Health Association收集的。研究设计:我们为每个HMO计算效率的三个估计值,并根据个人绩效和整个行业趋势比较结果。然后,根据案例组合,质量和可能与模型估计相关的其他因素的度量来对估计进行回归。主要发现:这三个模型为整个HMO行业确定了相似的趋势。但是,他们以不同的方式评估了各个公司的相对技术效率。因此,由于确定为有效的公司可能是模型选择的结果,而不是实际绩效,因此这些技术只能用于基准或设定利率。结论:评估有效公司的估计技术可能会影响调查结果本身。这些含义不仅与HMO有关,而且与总体效率分析有关。技术之间的并发不能保证准确性,但是可以放心。相反,模型之间截然不同的推论可能会警告研究结论。

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