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Measuring and forecasting quality in English hospitals

机译:衡量和预测英国医院的质量

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Hospital performance metrics, often in the form of risk-adjusted hospital mortality rates, are increasingly being made available in the public domain to compare hospitals. Despite the proliferation of these metrics, uncertainty remains regarding their validity and reliability given the noise surrounding their underlying measures. The paper considers a quality measure of hospital performance developed by McClellan and Staiger which smooths within hospitals and over time, while remaining computationally straightforward. The McClellan and Staiger method improves on others by incorporating different measures of outcome, eliminating systematic bias arising from the heterogeneous mix of hospital outputs and the noise that is inherent in other measures of quality. The technique also allows the forecasting of future quality. Using English hospital episode statistics for the years 2000-2005 for acute myocardial infarction and hip replacement, we use this technique to return quality measures based on hospital fixed effects estimated from yearly cross-sectional patient level data, and vector auto-regressions estimated over time, which then combine information from different time periods and across conditions to produce robust hospital quality measures. Our results suggest that this method is well suited to measure and predict provider quality of care in the English setting.
机译:医院绩效指标通常采用风险调整后的医院死亡率的形式,越来越多地在公共领域提供以比较医院。尽管这些指标激增,但由于其潜在指标周围存在噪音,其有效性和可靠性仍不确定。本文考虑了由McClellan和Staiger开发的医院绩效的质量度量标准,该度量标准可以在医院内并随着时间推移而平滑,同时保持计算上的直接性。 McClellan和Staiger方法通过采用不同的结果度量来改善其他方法,消除了医院产出的异质混合以及其他质量度量固有的噪声所引起的系统性偏差。该技术还可以预测未来的质量。使用2000-2005年英国急性心肌梗死和髋关节置换的医院发作统计数据,我们使用该技术基于根据每年的横断面患者水平数据估算出的医院固定效应以及随着时间推移估算出的向量自回归来返回质量测度,然后结合来自不同时间段和跨条件的信息,以生成可靠的医院质量度量。我们的结果表明,该方法非常适合在英语环境中衡量和预测提供者的护理质量。

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