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Benefit-of-the-doubt approaches for calculating a composite measure of quality

机译：不确定性收益方法，用于计算质量的综合度量

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Standard approaches for determining weights when calculating a composite measure of health care quality from individual quality indicators (QIs) include equal weighting, opportunity-based weights, and judgment-based weights. Benefit-of-the-doubt approaches have not been used in the health services area, though one has been used to calculate composite measures for profiling countries. Underlying these approaches is the assumption that relative performance on a set of indicators is, at least to some extent, a revealed preference by the organizational unit about the relative importance of the indicators. A benefit-of-the-doubt approach recognizes these revealed preferences by assigning higher weights to indicators on which performance is better and lower weights to indicators on which performance is poorer. We consider two benefit-of-the-doubt approaches. The first uses simple linear programming (LP) models; the second uses data envelopment analysis (DEA), the way in which the benefit-of-the-doubt approach has been previously implemented. In both cases, constraints are added to limit weight adjustments to some percentage of policy-determined baseline weights. Using both standard and benefit-of-the-doubt approaches, composite scores are calculated from data on five QIs from 32 Department of Veterans Affairs (VA) nursing homes. We examine the tradeoff between the level of allowable weight adjustment and impact on facility rankings. If weights are constrained to be within 75% of baseline weights, all approaches identify pretty much the same high performing facilities. Weights from benefit-of-the-doubt approaches, because they are able to reflect local preferences and conditions, should be attractive to facilities and, in a collaborative environment, to policy makers.
机译：根据单个质量指标（QIs）计算医疗质量的综合度量时，确定权重的标准方法包括相等权重，基于机会的权重和基于判断的权重。尽管已经使用一种不确定性的方法来计算概要分析国家的综合措施，但是在卫生服务领域并未使用这种方法。这些方法的基本假设是，至少在一定程度上，一组单位的相对绩效是组织单位明显偏爱指标的相对重要性。不确定性收益方法通过将较高的权重分配给绩效较好的指标，将较低的权重分配给绩效较差的指标来识别这些已揭示的偏好。我们考虑两种不确定性的方法。第一种使用简单的线性规划（LP）模型。第二种使用数据包络分析（DEA），这是先前已经实现的“不确定性收益”方法的方式。在这两种情况下，都添加了限制条件，以将权重调整限制为政策确定的基准权重的一定百分比。使用标准方法和不确定性收益方法，根据来自32个退伍军人事务部（VA）疗养院的五个QI的数据计算综合得分。我们研究了允许的重量调整水平与对设施等级的影响之间的权衡。如果将重量限制在基线重量的75％以内，则所有方法都将确定几乎相同的高性能设施。不确定性收益方法的权重，因为它们能够反映本地的偏好和条件，因此对于设施以及在协作环境中的决策者应该具有吸引力。

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