Statistical and Clinical Aspects of Hospital Outcomes Profiling

Hospital profiling involves a comparison of a health care provider's structure, processes of care, or outcomes to a standard, often in the form of a report card. Given the ubiquity of report cards and similar consumer ratings in contemporary American culture, it is notable that these are a relatively recent phenomenon in health care. Prior to the 1986 release of Medicare hospital outcome data, little such information was publicly available. We review the historical evolution of hospital profiling with special emphasis on outcomes; present a detailed history of cardiac surgery report cards, the paradigm for modern provider profiling; discuss the potential unintended negative consequences of public report cards; and describe various statistical methodologies for quantifying the relative performance of cardiac surgery programs. Outstanding statistical issues are also described.Comment: Published in at http://dx.doi.org/10.1214/088342307000000096 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Cost-Offsets of New Medications for Treatment of Schizophrenia

Broad claims are frequently made that new medications will offset all or part of their costs by reducing other areas of Medicaid spending. In this paper we examine the net impact on spending for new drugs used to treat schizophrenia. We extend research in this area by taking a new approach to identification of spending impacts of new drugs. We specify and estimate models of spending on treatment of schizophrenia using 7 years of Florida Medicaid data. The estimates indicate that use of the new drugs result in net spending increases. This may be due to increased adherence to treatment.

Real Output in Mental Health Care During the 1990s

Health accounts document changes over time in the level and composition of health spending. There has been a continued evolution in the ability to track such outlays. Less rapid has been the ability to interpret changes in spending. In this paper we apply quality adjusted price indexes for several major mental disorders to national mental health account estimates to assess changes in real "output". We show that using the new price indexes reveals large gains in real output relative to application of BLS indexes.

The Medical Treatment of Depression, 1991-1996: Productive Inefficiency, Expected Outcome Variations, and Price Indexes

We examine the price of treating episodes of acute phase major depression over the 1991-1996 time period. We combine data from a large retrospective medical claims data base (MarketScanTM, from the MedStat Group) with clinical literature and expert clinical opinion elicited from a two-state Delphi procedure. This enables us to construct a variety of treatment price indexes that include variations over time in the proportion of off-frontier' production, as well as the corresponding variations in expected treatment outcomes. We also incorporate the fact that the no treatment option ( waiting list') frequently results in spontaneous remission of depressive symptoms. We find that in general the incremental cost of successfully treating an episode of acute phase major depression has generally fallen over the 1991-96 time period. Based on hedonic regression equations that account for the effects of changing patient mix, we find price reductions that range from about -1.66% to -2.13% per year. An implication of this is that, since expenditures on depression are thought to be increasing since at least 1991, the source of the spending increases is volume (quantity) increases, and not price increases.

Handling incomplete correlated continuous and binary outcomes in meta‐analysis of individual participant data

Meta‐analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta‐analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta‐analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between‐study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta‐analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter‐defibrillator devices alone to implantable cardioverter‐defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd