Centers for Medicare and Medicaid Services (CMS) estimated that Medicare's Hospital-Acquired Condition Reduction Program (HAC-RP) would reduce hospital payments by $364 million in fiscal year 2016. Although observers have questioned the validity of certain HAC-RP measures, less attention has been paid to the determination of low-performing hospitals (bottom quartile) and the reliability of penalty assignment. This study used publicly available data from CMS's Hospital Compare to simulate the consistency of hospitals' scores and the assignment of penalties under repeated measurement with no change in each hospital's underlying quality. The simulation showed that 64.0% of all hospitals and 40.6% of hospitals subject to payment penalty are statistically significantly different from the penalty threshold at the 95% confidence level. The proportion of hospitals statistically different from the threshold showed significant variation by ownership status, teaching status, bed size, and other factors. The simulation further showed that due only to chance, 18.0% of penalized hospitals would escape penalty on repeated measurement. Policymakers should consider alterations to the HAC-RP to improve its reliability.
In 2016, Medicare's Hospital-Acquired Condition Reduction Program (HAC-RP) will reduce hospital payments by $364 million. Although observers have questioned the validity of certain HAC-RP measures, less attention has been paid to the determination of low-performing hospitals (bottom quartile) and the assignment of penalties. This study investigated possible bias in the HAC-RP by simulating hospitals' likelihood of being in the worst-performing quartile for 8 patient safety measures, assuming identical expected complication rates across hospitals. Simulated likelihood of being a poor performer varied with hospital size. This relationship depended on the measure's complication rate. For 3 of 8 measures examined, the equal-quality simulation identified poor performers similarly to empirical data (c-statistic approximately 0.7 or higher) and explained most of the variation in empirical performance by size (Efron's R > 0.85). The Centers for Medicare & Medicaid Services could address potential bias in the HAC-RP by stratifying by hospital size or using a broader "all-harm" measure.
Recent focus on the need to improve the quality and safety of health care has created new challenges for academic health centers (AHCs). Whereas previously quality was largely assumed, today it is increasingly quantifiable and requires organized systems for improvement. Traditional structures and cultures within AHCs, although well suited to the tripartite missions of teaching, research, and clinical care, are not easily adaptable to the tasks of measuring, reporting, and improving quality. Here, the authors use a case study of Massachusetts General Hospital's efforts to restructure quality and safety to illustrate the value of beginning with a focus on organizational culture, using a systematic process of engaging clinical leadership, developing an organizational framework dependent on proven business principles, leveraging focus events, and maintaining executive dedication to execution of the initiative. The case provides a generalizable example for AHCs of how applying explicit management design can foster robust organizational change with relatively modest incremental financial resources.
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