H. David Sherman

Bank branch operating efficiency : Evaluation with Data Envelopment Analysis

Abstract Measuring and evaluating the operating efficiency of bank branches requires analytic techniques that provide insights beyond those available from accounting ratio analysis. Data Envelopment Analysis (DEA), a mathematical programming technique, provides useful insights in locating inefficient branches by explicitly considering the mix of services provided and the resources used to provide these bank services. Bank management finds the DEA results provide meaningful insights not available from other techniques that focus on ways to improve productivity. The results suggests that DEA is a beneficial complement to other techniques for improving bank branch efficiency.

Hospital Efficiency Measurement and Evaluation: Empirical Test of a New Technique

A new technique for identifying inefficient hospitals, Data Envelopment Analysis (DEA), is field tested by application to a group of teaching hospitals. DEA is found to provide meaningful insights into the location and nature of hospital inefficiencies as judged by the opinion of a panel of hospital experts. DEA provides insights about hospital efficiency not available from the widely used efficiency evaluation techniques of ratio analysis and econometric-regression analysis. DEA is, therefore, suggested as a means to help identify and measure hospital inefficiency as a basis for directing management efforts toward increasing efficiency and reducing health care costs.

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.

DEA model with shared resources and efficiency decomposition

Data envelopment analysis (DEA) has proved to be an excellent approach for measuring performance of decision making units (DMUs) that use multiple inputs to generate multiple outputs. In many real world scenarios, DMUs have a two-stage network process with shared input resources used in both stages of operations. For example, in hospital operations, some of the input resources such as equipment, personnel, and information technology are used in the first stage to generate medical record to track treatments, tests, drug dosages, and costs. The same set of resources used by first stage activities are used to generate the second-stage patient services. Patient services also use the services generated by the first stage operations of housekeeping, medical records, and laundry. These DMUs have not only inputs and outputs, but also intermediate measures that exist in-between the two-stage operations. The distinguishing characteristic is that some of the inputs to the first stage are shared by both the first and second stage, but some of the shared inputs cannot be conveniently split up and allocated to the operations of the two stages. Recognizing this distinction is critical for these types of DEA applications because measuring the efficiency of the production for first-stage outputs can be misleading and can understate the efficiency if DEA fails to consider that some of the inputs generate other second-stage outputs. The current paper develops a set of DEA models for measuring the performance of two-stage network processes with non splittable shared inputs. An additive efficiency decomposition for the two-stage network process is presented. The models are developed under the assumption of variable returns to scale (VRS), but can be readily applied under the assumption of constant returns to scale (CRS). An application is provided.

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.

Do bank mergers have hidden or foregone value? Realized and unrealized operating synergies in one bank merger

Abstract Recent mergers in the banking industry have often generated disappointing shareholder returns. Delays in implementing potential operating savings and realizing benefits of scale economies may be one reason these mergers have disappointing returns. Using data envelopment analysis (DEA), we analyze a 200-branch network formed in a merger of four banks. The operating efficiency of each branch is benchmarked against “best-practice” branches in the combined merged bank as well as “best practice” branches within each pre-merger bank. This analysis identified opportunities to reduce branch operating costs by 22 percent for the entire merged bank. In contrast, the cost savings opportunity is under seven percent when analyzed within each pre-merger bank. These findings suggest benchmarking across the entire merged bank to identify the best practices bank-wide can generate added savings. However, in this bank merger, these merger benefits were not realized until four years after the merger. Interviews with key players in the merged bank indicate that the bank deferred realizing these benefits because of political pressures, personnel integration issues, system integration issues, and financial components of the merger such as restructuring reserves and the purchase price. These causes suggest areas where shareholders can and should demand more rapid improvement in performance of bank mergers and areas for future corporate merger research.

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.

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.

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.

Operations research in the public sector and nonprofit organizations

Public sector and nonprofit organizations (NPO) have been growing substantially in number and size since the turn of the millennium. In light of the ongoing economic crises these sectors are expected to grow even more with expanded demands for services, increased need for funds to meet the demands and need for their services, and increased pressure to use available funds efficiently and effectively. The purpose of operations research (OR) techniques is to improve organizations’ operations and achievements. We are pleased to include in this volume a group of high quality research papers, innovative case studies with OR applications to the public sector and NPO, all focusing on the objective of improving operations and achievements.