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Analytics and Decision Support in Health Care Operations Management -- Contents -- Tables & Figures -- Acknowledgments -- The Author -- Introduction -- Chapter-by-Chapter Revisions for the Third Edition -- Chapter 1: Introduction to Analytics and Decision Support in Health Care Operations Management -- Learning Objectives -- Historical Background and the Development of Decision Techniques -- The Health Care Manager and Decision Making -- Importance of Health Analytics: Information Technology (IT) and Decision Support Techniques -- The Scope of Health Care Services, and Recent Trends -- Health Care Services Management -- Distinctive Characteristics of Health Care Services -- Patient Participation -- Simultaneous Production and Consumption -- Perishable Capacity -- The Intangible Nature of Health Care Outputs -- The High Levels of Judgment Called Upon, and the Heterogeneous Nature of Health Care -- Big Data and Data Flow in Health Care Organizations -- Summary -- Key Terms -- Chapter 1 Supplement: Data Analytics in MS Excel: Creating and Manipulating Pivot Tables -- Exercises -- Chapter 2: Predictive Analytics -- Learning Objectives -- Steps in the Predictive Analytics Process -- Identify the Goal of the Predictive Analytics -- Establish a Time Horizon -- Select a Predictive Analytics Technique -- Conduct the Prediction -- Monitor Accuracy -- Predictive Analytics Techniques -- Judgmental Predictions -- Time-Series Technique -- Techniques for Averaging -- Techniques for Trend -- Predictive Techniques for Seasonality -- Accuracy of Predictive Analytics -- Prediction Control -- Summary -- Key Terms -- Exercises -- Chapter 3: Decision Making in Health Care -- Learning Objectives -- The Decision Process -- What Causes Poor Decisions? -- The Decision Level and Decision Milieu -- Decision Making under Uncertainty -- Payoff Table.

Free Clinics (FCs) in the United States contribute to the healthcare safety net by providing care to a variety of populations including the uninsured. Data Envelopment Analysis (DEA) is used to evaluate FC performance by examining clinic funding sources and the number of visits and prescriptions provided on an annual basis. Cross-sectional data including 48 Virginia FCs in 2010 are analyzed to distinguish efficient and inefficient FCs. In all, 30 clinics (62.5%) were found to be top performers and defined the efficiency frontier, whereas 18 clinics (37.5%) were evaluated as inefficient. On average, to obtain efficiency, inefficient clinics would annually need to increase the number of provided general medical visits by 2,183, specialty visits by 1,969, other visits by 1,495, and dispensed prescriptions by 7,305. These findings have implications for healthcare policy and FC management.

The 60 percent rule has served as a controversial policy change within the postacute care sector since its revision in 2004, requiring inpatient rehabilitation facilities (IRFs) to admit no less than 60% of patients according to 1 of 13 specific conditions or else risk the loss of IRF designation according to Medicare's prospective payment system. Using a contingency theory framework, this study proposes that the 60 percent rule introduced considerable uncertainty into freestanding IRFs' operational environment, and as a result, IRFs' operational performance varied according to their "fit" between certain structural characteristics and the pervasive environmental uncertainty. The results suggest that operational performance, as measured by facility Malmquist Index scores, decreased on average for freestanding IRFs following the 60 percent rule's enforcement in 2005. In contrast, organizations possessing structural characteristics that better "fit" the heightened environmental uncertainty exhibited improved performance on average during the study's 6-year time period.

This study evaluates the productivity changes for the Veterans Integrated Service Networks (VISNs) that the Veterans Health Administration (VHA) created, comparing performance in 1994 with that in 2004. This represents periods before and after the VHA in 1995 reconfigured provider units into 21 regionalized delivery systems and engaged in other important system innovations. Productivity is measured using the Malmquist Index approach (a longitudinal version of the data envelopment analysis [DEA]). Results indicate that the VISN restructuring generally produced improvements in overall productivity (Malmquist scores) and in VISN adaptations to structural/technological change. They also show that the VISNs overall did not produce "changes in efficiency," reflecting challenges they may have faced in making "technical change" through management adaptations. The findings are consistent with what would be expected, given the major changes that did occur within the VHA in recent years as well as the before and after design used in this study.

This study investigates how hospital electronic medical record (EMR) use influences quality performance. Data include nonfederal acute care hospitals in the United States. Sources of the data include the American Hospital Association, Hospital Quality Alliance, the Healthcare Information and Management Systems Society, and the Centers for Medicare and Medicaid Services case-mix index sets. The authors use a retrospective cross-sectional format with linear regression to assess the relationship between hospital EMR use and quality performance. Quality performance is measured using 10 process indicators related to 3 clinical conditions: acute myocardial infarction, congestive heart failure, and pneumonia. The authors also use a propensity score adjustment to control for possible selection bias. After this adjustment, the authors identify a positive significant relationship between EMR use and 4 of the 10 quality indicators. They conclude that there is limited evidence of the relationship between hospital EMR use and quality.

Thoroughly revised and updated for Excel®, this second edition of Quantitative Methods in Health Care Management offers a comprehensive introduction to quantitative methods and techniques for the student or new administrator. Its broad range of practical methods and analysis spans operational, tactical, and strategic decisions. Users will find techniques for forecasting, decision-making, facility location, facility layout, reengineering, staffing, scheduling, productivity, resource allocation, supply chain and inventory management, quality control, project management, queuing models for capacity, and simulation. The book's step-by-step approach, use of Excel, and downloadable Excel templates make the text highly practical. Praise for the Second Edition "The second edition of Dr. Ozcan's textbook is comprehensive and well-written with useful illustrative examples that give students and health care professionals a perfect toolkit for quantitative decision making in health care on the road for the twenty-first century. The text helps to explain the complex health care management problems and offer support for decision makers in this field."--Marion Rauner, associate professor, School of Business, Economics, and Statistics, University of Vienna. "Quantitative Methods in Health Care Administration, Second Edition covers a broad set of necessary and important topics. It is a valuable text that is easy to teach and learn from." -David Belson, professor, Department of Industrial Engineering, Viterbi School of Engineering, University of Southern California.

The authors identify the key organizational and environmental characteristics that influence the effectiveness and efficiency of publicly funded service organizations. In a study of 40 community mental health centers (CMHCs), they used fulfillment of community needs as a measure of effectiveness and utilization of various services as a measure of efficiency. The results indicate that client educational status, state facility utilization, minority population, personnel expense, management type, and board composition affect need fulfillment. The study also illuminates the relationship between efficiency and effectiveness of publicly funded service organizations. The findings suggest that the allocation of resources to these organizations from local, state, and federal governments tends to he based on the extent of unmet needs for services. That is, the less the publicly funded service organization meets community needs, the more government funds are allocated to meet the needs. If the unmet needs that stimulate higher levels of funding actually reflect inefficiency, the inverse relationship between effectiveness and efficiency suggests that the government's resource allocation may not be based on performance, but may in fact be rewarding inefficiency. The findings suggest that legitimacy does not enhance efficiency and that legitimacy and efficiency may be entirely independent, which is consistent with institutional theory. The study results will be of practical use to community leaders, taxpayers, consumer advocates, regulatory agencies, and managers of community mental health organizations.