Articles: outcome-assessment-health-care.
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Health services research · Oct 1991
Measuring outcomes of hospital care using multiple risk-adjusted indexes.
Using existing data sources, we developed three risk-adjusted measures of hospital quality: the risk-adjusted mortality index (RAMI), the risk-adjusted readmissions index (RARI), and the risk-adjusted complication index (RACI). We describe the construction and validation of each of these indexes. After these measures were developed, we tested the relationships among the three indexes using a sample of 300 hospitals. ⋯ This result provides some evidence that no measure of quality should be used by itself to represent different aspects of the quality of hospital care. Adequate overall measures of hospital quality will need to include multiple measures in order to be credible and to reflect the complexity of hospital care. The findings suggest that consumers, payers, and policymakers cannot simply choose one hospitalwide measure, such as the mortality rate, to validly represent a hospital's performance: those hospitals with high rankings on their mortality rates do not necessarily rank high on their readmission rates or complication rates.
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Despite advances in resuscitation, the ability to predict survival at cardiac arrests remains unsophisticated. We identified the factors determining outcome of all cardiopulmonary resuscitations performed at our institution over a 4-year period, and used a Cox multivariate regression model to design prognostic indices to assess the probability of successful resuscitation and hospital discharge. ⋯ The most influential variables, judged by the size and significance of their logistic regression coefficients, were rhythm, resuscitation delay, and age (for successful resuscitation), and rhythm, performance of intubation and defibrillation, defibrillation delay, and age (for survival until discharge). The combination of these in a prognostic index reliably predicted both outcome (area under the receiver operating curve of 0.78), and survival until discharge (area under the curve of 0.80).
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In this paper we consider whether methods currently used to measure utility of health outcomes are consistent with the equity criteria adopted by researchers. We show that unless the chosen equity criterion is incorporated in the design of the measurement instrument, the derived health state utilities are inconsistent with the equity criterion (except under special circumstances). Adjustment algorithms are derived, based on the axioms of von Neumann-Morgenstern utility theory, which take account of difference equity criteria currently adopted in the literature. The proposed approach is based on simple lottery questions of the type already used widely in empirical studies.