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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.
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.
Features of statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting-edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data-driven healthcare analytics in an effort to provide more personalized and smarter healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance healthcare quality and operational efficiency. Organized into two main sections, Part I features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient-monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part II focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: • Contributions from well-known international experts who shed light on new approaches in this growing area • Discussions on contemporary methods and techniques to address the handling of rich and large-scale healthcare data as well as the overall optimization of healthcare system operations • Numerous real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry • Plentiful applications that showcase analytical methods and tools tailored for successful healthcare systems modeling and improvement The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate-level courses typically offered within operations research, industrial engineering, business, and public health departments.
Health care costs in the United States exceed $3.5 trillion annually, with between $760 billion and $935 billion considered waste. Data-driven analytics could reduce costs and provide higher quality care to patients by more efficiently allocating limited resources, just as analytics has done in other industries such as logistics, manufacturing and aviation. In this dissertation, I demonstrate three levels at which analytics provide value in health: clinical decision making, healthcare operations management and public health policy. Clinical decision making refers to decisions at the individual patient level: for example, determining which treatment to provide a patient or predicting an individual's risk of disease. Healthcare operations management refers to decisions about the system that delivers care to patients: for example, determining how to organize patient flow through a hospital or schedule procedures. Finally, public health policy refers to decisions about the overall health of a population: for example, determining how to control an infectious disease or distribute limited resources across different diseases.
Operations management is increasingly a critical skill needed in today’s health care leader. Managing your organization’s complex interdisciplinary processes, labor and asset productivity, and operational performance involves quantitative and qualitative skills. Covering a range of topics from quality management to data analyses, Health Care Operations Management: A Systems Approach clearly explains the important concepts and skills necessary to lead a modern health care organization. Logically organized in four parts, Health Care Operations Management: A Systems Approach looks at operations, systems and financial management; methods for improving operations; analytical tools and technology; and health care supply chain. Thoroughly revised, the new Third Edition offers new content on health plan operations, use of information technology in operations management, and analytics – topics often overlooked in most health care operational management texts.
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.
The most up-to-date edition of the gold standard in health care information system references In the newly revised Fifth Edition of Health Care Information Systems, veteran healthcare information management experts and educators Karen A. Wager and Frances Wickham Lee, along with nationally-recognized leader in health information technology, John P. Glaser, deliver a one-stop resource for graduate and upper-level undergraduate students to gain the knowledge and develop the skills they need to manage information and information systems technology in the new healthcare environment. The latest edition sees its focus shift from the adoption of health care information systems and electronic health records to making effective use of health care data, information, and systems and optimizing their impact. New additions to this celebrated text include: Explorations of how health care information systems and information technology can be used to support national quality initiatives, value-based payment, population health management, and precision health and quality reporting Discussions of how issues like interoperability, electronic health record usability, and health IT safety are being (or not being) addressed Treatments of the roles played by data governance and analytics in clinical decision making and healthcare operations. Filled with case studies, supplemental resources, and engaging examinations of critical areas in health care information system use, management, implementation, and support, Health Care Information Systems is an ideal reference for students taking courses in business administration, public health, health administration, medicine, health informatics and health care management.
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.
Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by unveiling the causes for service disparity, such as spatio-temporal variations in wait times across different hospitals. The approach integrates four methods -- Structural Equation Modeling (SEM)-based analysis; integrated projection; service management strategy design and evaluation; and behavior-based autonomy-oriented modeling -- to address respective challenges encountered in performing data analytics and modeling studies on healthcare services. The thrust and uniqueness of this approach lies in the following aspects: Ability to explore underlying complex relationships between observed or latent impact factors and service performance. Ability to predict the changes and demonstrate the corresponding dynamics of service utilization and service performance. Ability to strategically manage service resources with the adaptation of unpredictable patient arrivals. Ability to figure out the working mechanisms that account for certain spatio-temporal patterns of service utilization and performance. To show the practical effectiveness of the proposed systematic approach, this book provides a series of pilot studies within the context of cardiac care in Ontario, Canada. The exemplified studies have unveiled some novel findings, e.g., (1) service accessibility and education may relieve the pressure of population size on service utilization; (2) functionally coupled units may have a certain cross-unit wait-time relationship potentially because of a delay cascade phenomena; (3) strategically allocating time blocks in operating rooms (ORs) based on a feedback mechanism may benefit OR utilization; (4) patients’ and hospitals’ autonomous behavior, and their interactions via wait times may bear the responsible for the emergence of spatio-temporal patterns observed in the real-world cardiac care system. Furthermore, this book presents an intelligent healthcare decision support (iHDS) system, an integrated architecture for implementing the data-driven complex systems modeling approach to developing, analyzing, investigating, supporting and advising healthcare related decisions. In summary, this book provides a data-driven systematic approach for addressing practical decision-support problems confronted in healthcare service management. This approach will provide policy makers, researchers, and practitioners with a practically useful way for examining service utilization and service performance in various ``what-if" scenarios, inspiring the design of effectiveness resource-allocation strategies, and deepening the understanding of the nature of complex healthcare service systems.
This thoroughly revised and updated second edition of Operations Management in Healthcare: Strategy and Practice describes how healthcare organizations can cultivate a competitive lead by developing superior operations using a strategic perspective. In clearly demonstrating the "how-tos" of effectively managing a healthcare organization, this new edition also addresses the "why" of providing quality and value-based care. Comprehensive and practice-oriented, chapters illustrate how to excel in the four competitive priorities - quality, cost, delivery, and flexibility - in order to build a cumulative model of healthcare operations in which all concepts and tools fit together. This textbook encourages a hands-on approach and integrates mind maps to connect concepts, icons for quick reference, dashboards for measurement and tracking of progress, and newly updated end-of-chapter problems and assignments to reinforce creative and critical thinking. Written with the diverse learning needs in mind for programs in health administration, public health, business administration, public administration, and nursing, the textbook equips students with essential high-level problem-solving and process improvement skills. The book reveals concepts and tools through a series of short vignettes of a fictitious healthcare organization as it embarks on its journey to becoming a highly reliable organization. This second edition also includes a strong emphasis on the patient's perspective as well as expanded and added coverage of Lean Six Sigma, value-based payment models, vertical integration, mergers and acquisitions, artificial intelligence, population health, and more to reflect evolving innovations in the healthcare environment across the United States. Complete with a full and updated suite of Instructor Resources, including Instructor’s Manual, PowerPoints, and test bank in addition to data sets, tutorial videos, and Excel templates for students. Key Features: Demonstrates the "how-tos" of effectively managing a healthcare organization Sharpens problem-solving and process improvement skills through use of an extensive toolkit developed throughout the text Prepares students for Lean Six Sigma certification with expanded coverage of concepts, tools, and analytics Highlights new trends in healthcare management with coverage of value-based payments, mergers and acquisitions, population health, telehealth, and more Intertwines concepts with vivid vignettes to describe human dynamics, organizational challenges, and applications of tools Employs boxed features and YouTube videos to address frequently asked questions and real-world instances of operations in practice