Jon A. Chilingerian

Evaluating physician efficiency in hospitals: A multivariate analysis of best practices

Abstract This paper reports on a six-month study of the clinical efficiency of 36 physicians in a single hospital. Both technical and scale efficiency are analyzed using Data Envelopment Analysis (DEA) and a multi-factor Tobit analysis is conducted to see which variables are associated with higher levels of physician performance. DEA identifies 24 inefficient physicians. The slack associated with these physicians supports the hypothesis that a substantial amount of money could be saved if every physician practiced medicine as efficiently as the most competent physicians. The Tobit analysis revealed two categories of technically efficient physicians: those who (1) belong to a health maintenance organization (HMO), or (2) specialize by diagnostic related groups (DRGs). Estimates of most productive output scale suggest that locally decreasing returns to scale set in at higher output levels for physicians who treat higher proportions of high severity patients. The results illustrate how blending DEA with censored regression can sharpen an analysis of best practices.

The effects of ownership, operating environment, and strategic choices on nursing home efficiency.

This article reports on a study of the labor efficiency of 461 nursing homes located in Pennsylvania. Data envelopment analysis was used to estimate efficiency scores. Tobit equations were estimated for the entire sample and for subsamples consisting of for-profit (FP) and not-for-profit (NFP) nursing homes. The authors found that the major factors explaining efficiency were managerial and environmental characteristics such as ownership, occupancy rate, size, payment source, wage rate, and per capita income, rather than quality characteristics of nursing homes. Analysis of the FP and NFP subsamples suggests that many NFP homes may respond to environmental pressures by increasing their efficiency, whereas FP homes tend to operate at a high level of efficiency irrespective of environmental and regulatory pressures.

Managing Physician Efficiency and Effectiveness in Providing Hospital Services

Physicians control more than 80 percent of the decisions affecting health costs. Consequently, managing physician practice patterns is an important avenue to reducing health care costs. One approach to identifying inefficient practice patterns is demonstrated in this pilot study of physicians treating heart shock patients. Physicians are evaluated using data envelopment analysis (DEA), a relatively new linear-program-based efficiency evaluation tool. This approach (1) locates physicians using excess resources in treating patients, (2) estimates the amount of excess resources used, and (3) explicitly considers the quality of patient care in the overall assessment of the physicians practice patterns. Findings of physician inefficiency that are stable over time could be used to alter practice patterns and subsequently to assist in cost containment.

Health-Care Applications: From Hospitals to Physicians, from Productive Efficiency to Quality Frontiers

This chapter focuses on health-care applications of DEA. The paper begins with a brief history of health applications and discusses some of the models and the motivation behind the applications. Using DEA to develop quality frontiers in health services is offered as a new and promising direction. The paper concludes with an eight-step application procedure and list of do’s and don’ts when applying DEA to health services.

DEA and primary care physician report cards: Deriving preferred practice cones from managed care service concepts and operating strategies

Evaluating the practice patterns of the newly dominant force in managed care, the primary care gatekeeper, will be one of the toughest challenges facing health reformers in the United States. This paper introduces DEA as a tool to profile and evaluate practice patterns of primary care physicians. To illustrate these ideas, the practice behavior of 326 primary care physicians in a large Health Maintenance Organization were studied for one year. When two DEA models were compared, a cone ratio DEA model projected the excess utilization of more hospital days and fewer office visits than a DEA model without defined preferred practice regions. The application demonstrates how a cone ratio DEA model can incorporate strategic thinking and executive accountability when establishing clinical benchmarks.

Estimating Hospital Inefficiency: Does Case Mix Matter?

A two-stage approach is used in a stochastic frontier analysis of the factors affecting hospital efficiency. In the first stage, a translog cost-function is used to estimate inefficiency scores. In the second stage, inefficiency scores are regressed against independent variables to test hypotheses that come from X-inefficiency Theory. The study was based on 1989 data for 195 Pennsylvania acute care hospitals. This data base was chosen because of the availability of patient-level severity of illness data, a measure of output that is not available from most data sources. The stochastic frontier analysis models estimated mean inefficiency scores that ranged from 0.075 to 0.180. The addition of the DRG case mix index (CMI) reduced estimated inefficiency by more than 50%. The incremental effect of a severity of illness variable to an equation with CMI was very small. The second-stage results suggest inefficiency and are inversely associated with regulatory pressures and industry concentration.

Benchmarking physician practice patterns with DEA: A multi-stage approach for cost containment

AbstractPhysician practice patterns in a Health Maintenance Organization (HMO) are analyzed using single and multi-stage applications of Data Envelopment Analysis (DEA). Best practice (BP) patterns are identified, which can serve as benchmark targets for inefficient physicians. Results suggest three health policy — resource utilization control strategies:(1)If managed care organizations could motivate primary care physicians to adopt the practice styles of the best practice primary care physicians, substantial clinical resource savings could be achieved, ranging from 12% to over 30% in the HMO that is the focus of this study;(2)some specialists who practice as primary care physicians (PCPs) provide more efficient care than some general practitioner PCPs, modifying the current perception that reducing specialists is the most effective way to achieve low cost practice patterns; and(3)groups of physicians in the HMO exhibit different resource use patterns, which may present opportunities to manage high cost groups as another path to contain costs. The results suggest specific new paths which may prove effective at reducing health care costs within managed care organizations, the health care providers most likely to dominate the U.S. health system in the future. A multi-stage DEA technique is used to locate specific types of inefficient physicians. Methods to test the clinical viability of using DEA to realize the potential cost savings and extensions of this research are discussed.

A CTSA Agenda to Advance Methods for Comparative Effectiveness Research

Clinical research needs to be more useful to patients, clinicians, and other decision makers. To meet this need, more research should focus on patient‐centered outcomes, compare viable alternatives, and be responsive to individual patients’ preferences, needs, pathobiology, settings, and values. These features, which make comparative effectiveness research (CER) fundamentally patient‐centered, challenge researchers to adopt or develop methods that improve the timeliness, relevance, and practical application of clinical studies.

Substance Abuse Treatment Organizations as Mediators of Social Policy: Slowing the Adoption of a Congressionally Approved Medication

Most substance abuse treatment occurs in outpatient treatment centers, necessitating an understanding of what motivates organizations to adopt new treatment modalities. Tichy’s framework of organizations as being comprised of three intertwined internal systems (technical, cultural, and political) was used to explain treatment organizations’ slow adoption of buprenorphine, a new medication for opiate dependence. Primary data were collected from substance abuse treatment organizations in four of the ten metropolitan areas with the largest number of heroin users. Only about one fifth offered buprenorphine. All three internal systems were important determinants of buprenorphine adoption in our multivariate model. However, the cultural system, measured by attitude toward medications, was a necessary condition for adoption. Health policies designed to encourage adoption of evidence-based performance measures typically focus on the technical system of organizations. These findings suggest that such policies would be more effective if they incorporate an understanding of all three internal systems.

Health Care Applications

This chapter focuses on health care applications of DEA. The paper begins with a brief history of health applications and discusses some of the models and the motivation behind the applications. Using DEA to develop quality frontiers in health services is offered as a new and promising direction. The paper concludes with an eight-step application procedure and list of Do’s and Don’ts when applying DEA to health services.