Thomas J W, Hofer T P
Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor 48109, USA.
Med Care. 1999 Jan;37(1):83-92. doi: 10.1097/00005650-199901000-00012.
Reports on hospital quality performance are being produced with increasing frequency by state agencies, commercial data vendors, and health care purchasers. Risk-adjusted mortality rate is the most commonly used measure of quality in these reports. The purpose of this study was to determine whether risk-adjusted mortality rates are valid indicators of hospital quality performance.
Based on an analytical model of random measurement error, sensitivity and predictive error of mortality rate indicators of hospital performance were estimated.
The following six parameters were shown to determine accuracy: (1) mortality risks of patients who receive good quality care and (2) of those who receive poor quality care, (3) proportion of patients (across all hospitals) who receive poor quality care, (4) proportion of hospitals considered to be "poor quality," (5) patients' relative risk of receiving poor quality care in "good quality" and in "poor quality" hospitals, and (6) number of patients treated per hospital. Using best available values for model parameters, analyses demonstrated that in nearly all situations, even with perfect risk adjustment, identifying poor quality hospitals on the basis of mortality rate performance is highly inaccurate. Of hospitals that delivered poor quality care, fewer than 12% were identified as high mortality rate outliers, and more than 60% of outliers were actually good quality hospitals.
Under virtually all realistic assumptions for model parameter values, sensitivity was less than 20% and predictive error was greater than 50%. Reports that measure quality using risk-adjusted mortality rates misinform the public about hospital performance.
州政府机构、商业数据供应商和医疗保健购买者越来越频繁地发布医院质量绩效报告。风险调整死亡率是这些报告中最常用的质量衡量指标。本研究的目的是确定风险调整死亡率是否是医院质量绩效的有效指标。
基于随机测量误差的分析模型，估计了医院绩效死亡率指标的敏感性和预测误差。
以下六个参数显示可决定准确性：（1）接受高质量护理的患者的死亡风险，（2）接受低质量护理的患者的死亡风险，（3）（所有医院中）接受低质量护理的患者比例，（4）被认为是“低质量”的医院比例，（5）患者在“高质量”和“低质量”医院接受低质量护理的相对风险，以及（6）每家医院治疗的患者数量。利用模型参数的最佳可用值进行分析表明，在几乎所有情况下，即使进行了完美的风险调整，根据死亡率表现来识别低质量医院也是极不准确的。在提供低质量护理的医院中，被识别为高死亡率异常值的不到12%，而超过60%的异常值实际上是高质量医院。
在几乎所有关于模型参数值的现实假设下，敏感性均低于20%，预测误差大于50%。使用风险调整死亡率来衡量质量的报告向公众提供了关于医院绩效的错误信息。
