Effective Treatment for Early-Stage Prostate Cancer — Possible, Necessary, or Both? by Matthew R. Smith (NEJM)
Radical Prostatectomy versus Watchful Waiting in Early Prostate Cancer, by Anna Bill-Axelson, et al. (NEJM)
BACKGROUND. In 2008, we reported that radical prostatectomy, as compared with watchful waiting, reduces the rate of death from prostate cancer. After an additional 3 years of follow-up, we now report estimated 15-year results.
METHODS. From October 1989 through February 1999, we randomly assigned 695 men with early prostate cancer to watchful waiting or radical prostatectomy. Follow-up was complete through December 2009, with histopathological review of biopsy and radical-prostatectomy specimens and blinded evaluation of causes of death. Relative risks, with 95% confidence intervals, were estimated with the use of a Cox proportional-hazards model.
RESULTS. During a median of 12.8 years, 166 of the 347 men in the radical-prostatectomy group and 201 of the 348 in the watchful-waiting group died (P=0.007). In the case of 55 men assigned to surgery and 81 men assigned to watchful waiting, death was due to prostate cancer. This yielded a cumulative incidence of death from prostate cancer at 15 years of 14.6% and 20.7%, respectively (a difference of 6.1 percentage points; 95% confidence interval [CI], 0.2 to 12.0), and a relative risk with surgery of 0.62 (95% CI, 0.44 to 0.87; P=0.01). The survival benefit was similar before and after 9 years of follow-up, was observed also among men with low-risk prostate cancer, and was confined to men younger than 65 years of age. The number needed to treat to avert one death was 15 overall and 7 for men younger than 65 years of age. Among men who underwent radical prostatectomy, those with extracapsular tumor growth had a risk of death from prostate cancer that was 7 times that of men without extracapsular tumor growth (relative risk, 6.9; 95% CI, 2.6 to 18.4).
CONCLUSIONS. Radical prostatectomy was associated with a reduction in the rate of death from prostate cancer. Men with extracapsular tumor growth may benefit from adjuvant local or systemic treatment.
The Pragmatist’s Guide to Comparative Effectiveness Research, by Amitabh Chandra, Anupam B. Jena, Jonathan S. Skinner (NBER)
All developed countries have been struggling with a trend toward health care absorbing an ever-larger fraction of government and private budgets. Adopting any treatment that improves health outcomes, no matter what the cost, can worsen allocative inefficiency by paying dearly for small health gains. One potential solution is to rely more heavily on studies of the costs and effectiveness of new technologies in an effort to ensure that new spending is justified by a commensurate gain in consumer benefits. But not everyone is a fan of such studies and we discuss the merits of comparative effectiveness studies and its cousin, cost-effectiveness analysis. We argue that effectiveness research can generate some moderating effects on cost growth in healthcare if such research can be used to nudge patients away from less-effective therapies, whether through improved decision making or by encouraging beefed-up copayments for cost-ineffective procedures. More promising still for reducing growth is the use of a cost-effectiveness framework to better understand where the real savings lie—and the real savings may well lie in figuring out the complex interaction and fragmentation of healthcare systems.
The Health Insurance Status of Low-Wage Workers: The Role of Workplace Composition and Marital Status, by Jessica Vistnes and Alan C. Monheit (MCRR)
Many of the provisions in the Affordable Care Act (ACA), such as tax credits and penalties for employers, vary by employer size and average wage level. Therefore, knowing the wage and firm size distribution of low-wage workers and how employer-sponsored insurance (ESI) characteristics vary by these dimensions is particularly important for understanding the extent to which low-wage workers and their employers may be affected by different provisions in the ACA. To inform this issue, the authors use data from the 2006 Medical Expenditure Panel Survey–Insurance Component to examine offers of coverage and cost-sharing requirements by the wage distribution and firm size dimensions of employers. They also draw on Medical Expenditure Panel Survey household-level data to describe the household circumstances of low-wage workers. The authors find that where low-wage workers are employed, who their colleagues are, and their spouses’ wage levels are important factors in determining low-wage workers’ access to coverage and the cost and generosity of such coverage.
The Effect of the MassHealth Hospital Pay-for-Performance Program on Quality, by Andrew M. Ryan and Jan Blustein (HSR)
Objective. To test the effect of Massachusetts Medicaid’s (MassHealth) hospital-based pay-for-performance (P4P) program, implemented in 2008, on quality of care for pneumonia and surgical infection prevention (SIP).
Data. Hospital Compare process of care quality data from 2004 to 2009 for acute care hospitals in Massachusetts (N=62) and other states (N=3,676) and American Hospital Association data on hospital characteristics from 2005.
Study Design. Panel data models with hospital fixed effects and hospital-specific trends are estimated to test the effect of P4P on composite quality for pneumonia and SIP. This base model is extended to control for the completeness of measure reporting. Further sensitivity checks include estimation with propensity-score matched control hospitals, excluding hospitals in other P4P programs, varying the time period during which the program was assumed to have an effect, and testing the program effect across hospital characteristics.
Principal Findings. Estimates from our preferred specification, including hospital fixed effects, trends, and the control for measure completeness, indicate small and nonsignificant program effects for pneumonia (−0.67 percentage points, p>.10) and SIP (−0.12 percentage points, p>.10). Sensitivity checks indicate a similar pattern of findings across specifications.
Conclusions. Despite offering substantial financial incentives, the MassHealth P4P program did not improve quality in the first years of implementation.
Changes in Per Member Per Month Expenditures after Implementation of Florida’s Medicaid Reform Demonstration, by Jeffrey S. Harman, Christy H. Lemak, Mona Al-Amin, Allyson G. Hall, and Robert Paul Duncan (HSR)
Objective. To determine the impact of Florida’s Medicaid Reform Demonstration on per member per month (PMPM) Medicaid expenditures.
Data. Florida Medicaid claims data from the two fiscal years before implementation of the Demonstration (FY0405, FY0506) and the first two fiscal years after implementation (FY0607, FY0708) from two reform counties and two nonreform counties.
Study Design. A difference-in-difference approach was used to compare changes in expenditures before and after implementation of reforms between the reform counties and the nonreform counties.
Data Extraction. Medicaid claims and eligibility files were extracted for enrollees in the reform and nonreform counties and collapsed into monthly amounts (N=16,875,467).
Principal Findings. When examining the entire population, the reforms had little impact on PMPM expenditures, particularly among SSI enrollees. PMPM expenditures for SSI enrollees increased by an additional U.S.$0.35 in the reform counties compared with the nonreform counties and increased by an additional U.S.$2.38 for Temporary Assistance for Needy Families (TANF) enrollees. An analysis that limited the sample to individuals with at least 3 or 6 months of observations pre- and postimplementation, however, showed reduced PMPM expenditures of U.S.$11.15–U.S.$19.44 PMPM for both the SSI and TANF populations.
Conclusions. Although Medicaid reforms in Florida did not result in significant reductions in PMPM expenditures when examining the full population, it does appear that expenditure reductions may be achieved among Medicaid enrollees with more stable enrollment, who have more exposure to managed care activities and may have more health care needs than the overall Medicaid population.