While hospitals can learn from other industries, they cannot be improved or run like factories. With work that is more individualized than standardized, and limited control over volume and arrivals, even the leanest-minded hospital must recognize that healthcare systems are more dynamic than nearly any work environment.Written with the creativity n

Hospital Capacity Management: Insights and Strategies details many of the key processes, procedures, and administrative realities that make up the healthcare system we all encounter when we visit the ED or the hospital. It walks through, in detail, how these systems work, how they came to be this way, why they are set up as they are, and then, in many cases, why and how they should be improved right now. Many examples pulled from the lifelong experiences of the authors, published studies, and well-documented case studies are provided, both to illustrate and support arguments for change. First and foremost, it is necessary to remember that the mission of our healthcare system is to take care of patients. This has been forgotten at times, causing many of the issues the authors discuss in the book including hospital capacity management. This facet of healthcare management is absolutely central to the success or failure of a hospital, both in terms of its delivery of care and its ability to survive as an institution. Poor hospital capacity management is a root cause of long wait times, overcrowding, higher error rates, poor communication, low satisfaction, and a host of other commonly experienced problems. It is important enough that when it is done well, it can completely transform an entire hospital system. Hospital capacity management can be described as optimizing a hospital’s bed availability to provide enough capacity for efficient, error-free patient evaluation, treatment, and transfer to meet daily demand. A hospital that excels at capacity management is easy to spot: no lines of people waiting and no patients in hallways or sitting around in chairs. These hospitals don’t divert incoming ambulances to other hospitals; they have excellent patient safety records and efficiently move patients through their organization. They exist but are sadly in the minority of American hospitals. The vast majority are instead forced to constantly react to their own poor performance. This often results in the building of bigger and bigger institutions, which, instead of managing capacity, simply create more space in which to mismanage it. These institutions are failing to resolve the true stumbling blocks to excellent patient care, many of which you may have experienced firsthand in your own visit to your hospital. It is the hope of the authors that this book will provide a better understanding of the healthcare delivery system.

Our nation's capacity to care is becoming increasingly stressed as an aging and increasingly unhealthy population collides with a relative reduction in the numbers of clinicians and ever-tightening financial resources. If even the mildest of future-state predictions are to be believed, we need a significant restructuring of our entire healthcare system and its total Capacity to Care, such that we can simultaneously improve care capacity, cost, quality, accessibility, and resource gratification. Optimizing Your Capacity to Care: A Systems Approach to Hospital and Population Health Management provides comprehensive guidance to a new way to optimize and manage community-wide Care Capacity via a unique, holistic approach to healthcare operations. Through clear examples and actual project results, the book demonstrates the outcomes of a systems-level way of thinking about a community's Capacity to Care that incorporates and integrates the full spectrum of available clinical and communal resources into the care of patients, including hospitals, physicians, emergency departments, surgical services, local churches, civic organizations, pharmacies, and volunteers. The book details operational models for each major department of the hospital and a fully integrated communal resource pool to demonstrate how the optimization of capacity, resource utilization, cost, and clinical outcomes can be attained. And by providing healthcare leaders with a deeper understanding of key elements missing from the most common process improvement methodologies and approaches, this book offers fresh perspectives and bold alternatives for hospitals, health systems, and entire communities.

In both rich and poor nations, public resources for health care are inadequate to meet demand. Policy makers and health care providers must determine how to provide the most effective health care to citizens using the limited resources that are available. This chapter describes current and future challenges in the delivery of health care, and outlines the role that operations research (OR) models can play in helping to solve those problems. The chapter concludes with an overview of this book – its intended audience, the areas covered, and a description of the subsequent chapters. KEY WORDS Health care delivery, Health care planning HEALTH CARE DELIVERY: PROBLEMS AND CHALLENGES 3 1.1 WORLDWIDE HEALTH: THE PAST 50 YEARS Human health has improved significantly in the last 50 years. In 1950, global life expectancy was 46 years [1]. That figure rose to 61 years by 1980 and to 67 years by 1998 [2]. Much of these gains occurred in low- and middle-income countries, and were due in large part to improved nutrition and sanitation, medical innovations, and improvements in public health infrastructure.

Although much has been achieved in care coordination and accountable care, healthcare leaders need additional, game-changing innovations to deal with constraints in clinical resources, care capacity, and cost that have not yet been fully addressed. This need for innovation is especially great in the care of the chronically ill: the most costly, hig

Although much has been achieved in care coordination and accountable care, healthcare leaders need additional, game-changing innovations to deal with constraints in clinical resources, care capacity, and cost that have not yet been fully addressed. This need for innovation is especially great in the care of the chronically ill: the most costly, hig

Measuring Capacity to Care Using Nursing Data presents evidence-based solutions regarding the adoption of safe staffing principles and the optimum use of operational data to enable health service delivery strategies that result in improved patient and organizational outcomes. Readers will learn how to make better use of informatics to collect, share, link and process data collected operationally for the purpose of providing real-time information to decision- makers. The book discusses topics such as dynamic health care environments, health care operational inefficiencies and costly events, how to measure nursing care demand, nursing models of care, data quality and governance, and big data. The content of the book is a valuable source for graduate students in informatics, nurses, nursing managers and several members involved in health care who are interested in learning more about the beneficial use of informatics for improving their services. Presents and discusses evidences from real-world case studies from multiple countries Provides detailed insights of health system complexity in order to improve decision- making Demonstrates the link between nursing data and its use for efficient and effective healthcare service management Discusses several limitations currently experienced and their impact on health service delivery

From the Preface: Collectively, the chapters in this book address application domains including inpatient and outpatient services, public health networks, supply chain management, and resource constrained settings in developing countries. Many of the chapters provide specific examples or case studies illustrating the applications of operations research methods across the globe, including Africa, Australia, Belgium, Canada, the United Kingdom, and the United States. Chapters 1-4 review operations research methods that are most commonly applied to health care operations management including: queuing, simulation, and mathematical programming. Chapters 5-7 address challenges related to inpatient services in hospitals such as surgery, intensive care units, and hospital wards. Chapters 8-10 cover outpatient services, the fastest growing part of many health systems, and describe operations research models for primary and specialty care services, and how to plan for patient no-shows. Chapters 12 – 16 cover topics related to the broader integration of health services in the context of public health, including optimizing the location of emergency vehicles, planning for mass vaccination events, and the coordination among different parts of a health system. Chapters 17-18 address supply chain management within hospitals, with a focus on pharmaceutical supply management, and the challenges of managing inventory for nursing units. Finally, Chapters 19-20 provide examples of important and emerging research in the realm of humanitarian logistics.

A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.

This book demonstrates how to successfully manage and lead healthcare institutions by employing the logic of business model innovation to gain competitive advantages. Since clerk-like routines in professional organizations tend to overlook patient and service-centered healthcare solutions, it challenges the view that competition and collaboration in the healthcare sector should not only incorporate single-end services, therapies or diagnosis related groups. Moreover, the authors focus on holistic business models, which place greater emphasis on customer needs and put customers and patients first. The holistic business models approach addresses topics such as business operations, competitiveness, strategic business objectives, opportunities and threats, critical success factors and key performance indicators.The contributions cover various aspects of service business innovation such as reconfiguring the hospital business model in healthcare delivery, essential characteristics of service business model innovation in healthcare, guided business modeling and analysis for business professionals, patient-driven service delivery models in healthcare, and continuous and co-creative business model creation. All of the contributions introduce business models and strategies, process innovations, and toolkits that can be applied at the managerial level, ensuring the book will be of interest to healthcare professionals, hospital managers and consultants, as well as scholars, whose focus is on improving value-generating and competitive business architectures in the healthcare sector.