Shahian David M, Normand Sharon-Lise T
Center for Quality and Safety, Department of Surgery, and Institute for Health Policy, Massachusetts General Hospital, and Harvard Medical School, Boston, MA 02115, USA.
Circulation. 2008 Apr 15;117(15):1955-63. doi: 10.1161/CIRCULATIONAHA.107.747873. Epub 2008 Apr 7.
A frequent challenge in outcomes research is the comparison of rates from different populations. One common example with substantial health policy implications involves the determination and comparison of hospital outcomes. The concept of "risk-adjusted" outcomes is frequently misunderstood, particularly when it is used to justify the direct comparison of performance at 2 specific institutions.
Data from 14 Massachusetts hospitals were analyzed for 4393 adults undergoing isolated coronary artery bypass graft surgery in 2003. Mortality estimates were adjusted using clinical data prospectively collected by hospital personnel and submitted to a data coordinating center designated by the state. The primary outcome was hospital-specific, risk-standardized, 30-day all-cause mortality after surgery. Propensity scores were used to assess the comparability of case mix (covariate balance) for each Massachusetts hospital relative to the pool of patients undergoing coronary artery bypass grafting surgery at the remaining hospitals and for selected pairwise comparisons. Using hierarchical logistic regression, we indirectly standardized the mortality rate of each hospital using its expected rate. Predictive cross-validation was used to avoid underidentification of true outlying hospitals. Overall, there was sufficient overlap between the case mix of each hospital and that of all other Massachusetts hospitals to justify comparison of individual hospital performance with that of the remaining hospitals. As expected, some pairwise hospital comparisons indicated lack of comparability. This finding illustrates the fallacy of assuming that risk adjustment per se is sufficient to permit direct side-by-side comparison of healthcare providers. In some instances, such analyses may be facilitated by the use of propensity scores to improve covariate balance between institutions and to justify such comparisons.
Risk-adjusted outcomes, commonly the focus of public report cards, have a specific interpretation. Using indirect standardization, these outcomes reflect a provider's performance for its specific case mix relative to the expected performance of an average provider for that same case mix. Unless study design or post hoc adjustments have resulted in reasonable overlap of case-mix distributions, such risk-adjusted outcomes should not be used to directly compare one institution with another.
结果研究中一个常见的挑战是比较不同人群的发生率。一个具有重大卫生政策意义的常见例子涉及医院结果的确定和比较。“风险调整”结果的概念经常被误解,尤其是当它被用于证明对两个特定机构的绩效进行直接比较时。
分析了2003年马萨诸塞州14家医院4393例接受单纯冠状动脉搭桥手术的成年患者的数据。使用医院工作人员前瞻性收集并提交给该州指定的数据协调中心的临床数据对死亡率估计值进行调整。主要结局是特定医院、风险标准化的术后30天全因死亡率。倾向得分用于评估每家马萨诸塞州医院相对于其余医院接受冠状动脉搭桥手术患者群体的病例组合可比性(协变量平衡),以及进行选定的成对比较。使用分层逻辑回归,我们用每家医院的预期死亡率间接标准化其死亡率。采用预测性交叉验证以避免对真正的异常值医院识别不足。总体而言,每家医院与所有其他马萨诸塞州医院的病例组合之间有足够的重叠,足以证明将各医院的绩效与其余医院的绩效进行比较是合理的。正如预期的那样,一些成对的医院比较表明缺乏可比性。这一发现说明了认为风险调整本身足以允许对医疗服务提供者进行直接并列比较的错误观念。在某些情况下,使用倾向得分来改善机构间的协变量平衡并证明此类比较的合理性可能有助于此类分析。
风险调整后的结果通常是公共成绩单的重点,有特定的解释。使用间接标准化,这些结果反映了提供者相对于同一病例组合的平均提供者预期绩效而言,其特定病例组合的绩效。除非研究设计或事后调整导致病例组合分布有合理的重叠,否则此类风险调整后的结果不应直接用于比较一个机构与另一个机构。