Staiger Douglas O, Dimick Justin B, Baser Onur, Fan Zhaohui, Birkmeyer John D
Department of Economics and the Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Hanover, New Hampshire, USA.
Med Care. 2009 Feb;47(2):226-33. doi: 10.1097/MLR.0b013e3181847574.
Individual quality measures have significant limitations for assessing surgical performance. Despite growing interest in composite measures, empirically-based methods for combining multiple domains of surgical quality are not well established.
To develop and validate a composite measure of surgical performance that best describes variation in hospital mortality rates and forecasts future performance.
Using the national Medicare claims database, we identified all patients undergoing aortic valve replacement in 2000 to 2001 (n = 53,120). To serve as input variables, we identified hospital-level predictors of mortality with aortic valve replacement, including hospital volume, complication rates, and mortality with other procedures. Hospital-specific predicted mortality rates were then determined using Bayesian-derived modeling techniques and assessed against subsequent hospital mortality (2002-2003).
Our composite measure explained 78% of the variation in aortic valve replacement mortality rates (2000-2001). The most important input variables were hospital volume, mortality with aortic valve replacement, and mortality for other high-risk cardiac procedures. The composite measure forecasted 70% of future hospital-level variation in mortality rates (2002-2003), and was substantially better in this regard than individual measures. Hospitals scoring in the bottom quintile on the composite measure in 2000 to 2001 had 2-fold higher mortality rates in 2002 to 2003 than hospitals in the top quintile (adjusted odds ratio, 1.97; 95% CI, 1.73-2.23).
Compared with individual surgical quality indicators, empirically derived composite measures are superior in explaining variation in hospital mortality rates and in forecasting future performance. Such measures could be useful for public reporting, value-based purchasing, or benchmarking for quality improvement purposes.
个体质量指标在评估手术表现方面存在重大局限性。尽管对综合指标的兴趣日益浓厚，但基于实证的综合多个手术质量领域的方法尚未得到充分确立。
开发并验证一种能最佳描述医院死亡率差异并预测未来表现的手术表现综合指标。
利用国家医疗保险索赔数据库，我们识别出2000年至2001年期间所有接受主动脉瓣置换术的患者（n = 53,120）。作为输入变量，我们确定了主动脉瓣置换术死亡率的医院层面预测因素，包括医院手术量、并发症发生率以及其他手术的死亡率。然后使用贝叶斯推导建模技术确定特定医院的预测死亡率，并与随后的医院死亡率（2002 - 2003年）进行对比评估。
我们的综合指标解释了主动脉瓣置换术死亡率（2000 - 2001年）差异的78%。最重要的输入变量是医院手术量、主动脉瓣置换术死亡率以及其他高风险心脏手术的死亡率。该综合指标预测了70%的未来医院层面死亡率差异（2002 - 2003年），在这方面比个体指标显著更好。在2000年至2001年综合指标得分处于最低五分位数的医院，其2002年至2003年的死亡率比处于最高五分位数的医院高出两倍（调整后的优势比为1.97；95%置信区间为1.73 - 2.23）。
与个体手术质量指标相比，基于实证得出的综合指标在解释医院死亡率差异和预测未来表现方面更具优势。此类指标可用于公开报告、基于价值的采购或用于质量改进目的的基准设定。
