Meredith B Rosenthal, Bruce E Landon, Sharon-Lise T Normand, Richard G Frank, and Arnold M Epstein. 2006. “
Pay for performance in commercial HMOs.” N Engl J Med, 355, 18, Pp. 1895-902.
AbstractBACKGROUND: Pay for performance has increasingly become the subject of intense interest and debate, both of which have been heightened as the Centers for Medicare and Medicaid Services moves closer to adopting this approach for Medicare. Although many claims have been made for the effectiveness of this approach, the extent of its national penetration remains unknown.
METHODS: We surveyed a sample of 252 health maintenance organizations (HMOs) (response rate, 96%) drawn from 41 metropolitan areas across the nation about use of pay for performance. We determined the prevalence of pay-for-performance programs, detailed the features of such programs, and examined the adoption of pay for performance as a function of the characteristics of both the health plans and markets.
RESULTS: More than half the HMOs, representing more than 80% of persons enrolled, use pay for performance in their provider contracts. Of the 126 health plans with pay-for-performance programs, nearly 90% had programs for physicians and 38% had programs for hospitals. Use of pay for performance was statistically associated with geographic region, use of primary care providers (PCPs) as gatekeepers, use of capitation to pay PCPs, and whether the plans themselves received bonuses or penalties according to performance.
CONCLUSIONS: Pay for performance is now commonly used by HMOs, especially those that are situated to assign responsibility for a particular patient to a PCP or medical group. As the design of Medicare with pay for performance moves forward, it will be important to leverage the early experience of pay for performance in the commercial market.
Bruce E Landon, Sharon-Lise T Normand, Adam Lessler, James A O'Malley, Stephen Schmaltz, Jerod M Loeb, and Barbara J McNeil. 2006. “
Quality of care for the treatment of acute medical conditions in US hospitals.” Arch Intern Med, 166, 22, Pp. 2511-7.
AbstractBACKGROUND: The Joint Commission on Accreditation of Healthcare Organizations and the Centers for Medicare and Medicaid Services recently began reporting on quality of care for acute myocardial infarction, congestive heart failure, and pneumonia.
METHODS: We linked performance data submitted for the first half of 2004 to American Hospital Association data on hospital characteristics. We created composite scales for each disease and used factor analysis to identify 2 additional composites based on underlying domains of quality. We estimated logistic regression models to examine the relationship between hospital characteristics and quality.
RESULTS: Overall, 75.9% of patients hospitalized with these conditions received recommended care. The mean composite scores and their associated interquartile ranges were 0.85 (0.81-0.95), 0.64 (0.52-0.78), and 0.88 (0.80-0.97) for acute myocardial infarction, congestive heart failure, and pneumonia, respectively. After adjustment, for-profit hospitals consistently underperformed not-for-profit hospitals for each condition, with odds ratios (ORs) ranging from 0.79 (95% confidence interval [CI], 0.78-0.80) for the congestive heart failure composite measure to 0.90 (95% CI, 0.89-0.91) for the pneumonia composite. Major teaching hospitals had better performance on the treatment and diagnosis composite (OR, 1.37; 95% CI, 1.34-1.39) but worse performance on the counseling and prevention composite (OR, 0.83; 95% CI, 0.82-0.84). Hospitals with more technology available, higher registered nurse staffing, and federal/military designation had higher performance.
CONCLUSIONS: Patients are more likely to receive high-quality care in not-for-profit hospitals and in hospitals with high registered nurse staffing ratios and more investment in technology. Because payments and sources of payments affect some of these factors (eg, investments in technology and staffing ratios), policy makers should evaluate the effect of alternative payment approaches on quality.
Rusty Tchernis, Sharon-Lise T Normand, Juliana Pakes, Peter Gaccione, and Joseph P Newhouse. 2006. “
Selection and plan switching behavior.” Inquiry, 43, 1, Pp. 10-22.
AbstractA majority of employees can choose among health insurance plans of varying generosity. They may switch plans if prices, information, or their health status change. This paper analyzes switching behavior presumptively caused by changes in health status. We show that people who move to a less generous plan have lower medical spending prior to the switch than the average for the generous plan in which they started, while those who move to a more generous plan appear to anticipate higher spending, which they delay until after the switch. This transfer of costs from a less to a more generous plan increases the burden of adverse selection. Our data suggest that switching may be more important to the level of premiums than previously documented.
Harlan M Krumholz, Ralph G Brindis, John E Brush, David J Cohen, Andrew J Epstein, Karen Furie, George Howard, Eric D Peterson, Saif S Rathore, Sidney C Smith, John A Spertus, Yun Wang, and Sharon-Lise T Normand. 2006. “
Standards for statistical models used for public reporting of health outcomes: an American Heart Association Scientific Statement from the Quality of Care and Outcomes Research Interdisciplinary Writing Group: cosponsored by the Council on Epidemiology an.” Circulation, 113, 3, Pp. 456-62.
AbstractWith the proliferation of efforts to report publicly the outcomes of healthcare providers and institutions, there is a growing need to define standards for the methods that are being employed. An interdisciplinary writing group identified 7 preferred attributes of statistical models used for publicly reported outcomes. These attributes include (1) clear and explicit definition of an appropriate patient sample, (2) clinical coherence of model variables, (3) sufficiently high-quality and timely data, (4) designation of an appropriate reference time before which covariates are derived and after which outcomes are measured, (5) use of an appropriate outcome and a standardized period of outcome assessment, (6) application of an analytical approach that takes into account the multilevel organization of data, and (7) disclosure of the methods used to compare outcomes, including disclosure of performance of risk-adjustment methodology in derivation and validation samples.
Niteesh K Choudhry, Stephen B Soumerai, Sharon-Lise T Normand, Dennis Ross-Degnan, Andreas Laupacis, and Geoffrey M Anderson. 2006. “
Warfarin prescribing in atrial fibrillation: the impact of physician, patient, and hospital characteristics.” Am J Med, 119, 7, Pp. 607-15.
AbstractPURPOSE: The study investigated the determinants of warfarin use in patients with atrial fibrillation (AF).
METHODS: We assembled a retrospective cohort of community-dwelling elderly patients (aged > or = 66 years) with AF using linked administrative databases. We identified the physicians responsible for the ambulatory care of these patients using physician service claims and compared patients who did and did not have an identifiable provider. For those patients with an identifiable provider, we assessed the association between patient, physician, and hospital factors and warfarin use.
RESULTS: Our cohort consisted of 140,185 patients, of whom 116,200 (83%) had an identifiable cardiac provider. Patients without a provider were significantly more likely to have comorbid conditions that increase their risk of warfarin-associated bleeding. After adjustment for clinical factors, patients without a provider were significantly less likely to receive warfarin (odds ratio 0.37, 95% confidence interval: 0.36-0.38). Of patients with providers, 50,551 patients (43.5%) received warfarin within 180 days after hospital discharge. Warfarin use was positively associated with AF-associated stroke risk factors (eg, prior stroke, congestive heart failure) and negatively associated with warfarin-associated bleeding risk factors (eg, history of intracerebral hemorrhage). After controlling for patient and hospital factors, patients cared for by noncardiologist physicians with cardiology consultation were more likely to receive warfarin then patients treated in noncollaborative environments.
CONCLUSIONS: Warfarin continues to be substantially underprescribed to patients who are at high risk for AF-associated cardioembolic stroke. Our findings highlight the need for targeted quality improvement interventions and suggest preferred models of AF care involving routine collaboration between cardiologists and other physicians.