Analytics And Decision Support In Health Care Operations Management

A compendium of health care quantitative techniques based in Excel Analytics and Decision Support in Health Care Operations is a comprehensive introductory guide to quantitative techniques, with practical Excel-based solutions for strategic health care management. This new third edition has been extensively updated to reflect the continuously evolving field, with new coverage of predictive analytics, geographical information systems, flow process improvement, lean management, six sigma, health provider productivity and benchmarking, project management, simulation, and more. Each chapter includes additional new exercises to illustrate everyday applications, and provides clear direction on data acquisition under a variety of hospital information systems. Instructor support includes updated Excel templates, PowerPoint slides, web based chapter end supplements, and data banks to facilitate classroom instruction, and working administrators will appreciate the depth and breadth of information with clear applicability to everyday situations. The ability to use analytics effectively is a critical skill for anyone involved in the study or practice of health services administration. This book provides a comprehensive set of methods spanning tactical, operational, and strategic decision making and analysis for both current and future health care administrators. Learn critical analytics and decision support techniques specific to health care administration Increase efficiency and effectiveness in problem-solving and decision support Locate appropriate data in different commonly-used hospital information systems Conduct analyses, simulations, productivity measurements, scheduling, and more From statistical techniques like multiple regression, decision-tree analysis, queuing and simulation, to field-specific applications including surgical suite scheduling, roster management, quality monitoring, and more, analytics play a central role in health care administration. Analytics and Decision Support in Health Care Operations provides essential guidance on these critical skills that every professional needs.

This textbook is a logical continuation of Dr. Tan's first book, Healt h Management Information Systems. For graduate level and upper level u ndergraduate courses, it explains the use of health decision support s ystems throughout the health care industry, citing examples from hospi tals, managed care organizations and long term care facilities. This b ook includes learning objectives, case studies and review questions. A n Instructor's guide is also available.

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.

Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.

Health Care Operations Management: A Systems Perspective, Second Edition provides comprehensive and practical coverage of all aspects of operations management specific to the healthcare industry. It covers everything from hospital finances to project management, patient flows, performance management, process improvement, and supply chain management. This is an ideal text for university courses in healthcare management at all levels. It is also an excellent professional reference for healthcare administrators, clinical support managers, and supply chain professionals. The Second Edition has been thoroughly updated with the most recent data, statistics, and references. It also offers expanded coverage of quality, financial, and systems management, as well as a new chapter entitled "Operational Metrics in Health Care Organization".

This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are essential in today’s world. Healthcare management faces a number of challenges, e.g. reducing patient growth through disease prevention, stopping or slowing disease progression, and reducing healthcare costs while improving quality of care. The book provides an overview of current healthcare management problems and highlights how analytics and knowledge management have been used to better cope with them. It then demonstrates how to use descriptive and predictive analytics tools to help address these challenges. In closing, it presents applications of software solutions in the context of healthcare management. Given its scope, the book will appeal to a broad readership, from researchers and students in the operations research and management field to practitioners such as data analysts and decision-makers who work in the healthcare sector.

How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century? Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline. The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts. The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook: Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose. The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

This Briefs Series book illustrates in depth a concept of healthcare management engineering and its domain for hospital and clinic operations. Predictive and analytic decision-making power of management engineering methodology is systematically compared to traditional management reasoning by applying both side by side to analyze 26 concrete operational management problems adapted from hospital and clinic practice. The problem types include: clinic, bed and operating rooms capacity; patient flow; staffing and scheduling; resource allocation and optimization; forecasting of patient volumes and seasonal variability; business intelligence and data mining; and game theory application for allocating cost savings between cooperating providers. Detailed examples of applications are provided for quantitative methods such as discrete event simulation, queuing analytic theory, linear and probabilistic optimization, forecasting of a time series, principal component decomposition of a data set and cluster analysis, and the Shapley value for fair gain sharing between cooperating participants. A summary of some fundamental management engineering principles is provided. The goal of the book is to help to bridge the gap in mutual understanding and communication between management engineering professionals and hospital and clinic administrators. The book is intended primarily for hospital/clinic leadership who are in charge of making managerial decisions. This book can also serve as a compendium of introductory problems/projects for graduate students in Healthcare Management and Administration, as well as for MBA programs with an emphasis in Healthcare.