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Author: Asli Özen Publisher: ISBN: Category : Health care reform Languages : en Pages : 255
Book Description
U.S. healthcare system has become far too complex and costly to sustain and operations research has much to contribute in improving health systems by addressing a large spectrum of problems. We study capacity planning in healthcare while considering the case-mix of patients, using stochastic modeling in different application areas: primary care, inpatient bed allocation and (spine) surgery scheduling. This body of work was developed over four years of collaborative research with hospitals and healthcare providers. The main objective of our research in primary care is to optimize the patient mix of primary care physicians in a group practice to maximize patient-clinician continuity and access. To model case-mix, we use the number of simultaneous chronic conditions (comorbidities) a patient has as a predictor of the number of appointment requests. We later extend the optimization framework and use queuing theory to develop methodologies to quantify and evaluate access to care and continuity of care for patient visits with different urgencies. From an inpatient care perspective, we develop an empirically calibrated simulation model to represent a time-varying multi-server queuing network model with multiple patient classes. Our main focus has been on quantifying the impact of discharge profiles to alleviate inpatient bed congestions. The main objective of our research in surgical care is to create better patient access and improve revenue as a result of increased surgical capacity with more efficient schedules and an improved patient mix, using a multi-stage mixed integer optimization.
Author: Asli Özen Publisher: ISBN: Category : Health care reform Languages : en Pages : 255
Book Description
U.S. healthcare system has become far too complex and costly to sustain and operations research has much to contribute in improving health systems by addressing a large spectrum of problems. We study capacity planning in healthcare while considering the case-mix of patients, using stochastic modeling in different application areas: primary care, inpatient bed allocation and (spine) surgery scheduling. This body of work was developed over four years of collaborative research with hospitals and healthcare providers. The main objective of our research in primary care is to optimize the patient mix of primary care physicians in a group practice to maximize patient-clinician continuity and access. To model case-mix, we use the number of simultaneous chronic conditions (comorbidities) a patient has as a predictor of the number of appointment requests. We later extend the optimization framework and use queuing theory to develop methodologies to quantify and evaluate access to care and continuity of care for patient visits with different urgencies. From an inpatient care perspective, we develop an empirically calibrated simulation model to represent a time-varying multi-server queuing network model with multiple patient classes. Our main focus has been on quantifying the impact of discharge profiles to alleviate inpatient bed congestions. The main objective of our research in surgical care is to create better patient access and improve revenue as a result of increased surgical capacity with more efficient schedules and an improved patient mix, using a multi-stage mixed integer optimization.
Author: Jingshan Li Publisher: World Scientific ISBN: 9813220864 Category : Medical Languages : en Pages : 322
Book Description
In recent years, there has been an increased interest in the field of healthcare delivery systems. Scientists and practitioners are constantly searching for ways to improve the safety, quality and efficiency of these systems in order to achieve better patient outcome.This book focuses on the research and best practices in healthcare engineering and technology assessment. With contributions from researchers in the fields of healthcare system stochastic modeling, simulation, optimization and management, this is a valuable read.
Author: Chin-I. Lin Publisher: ISBN: Category : Languages : en Pages :
Book Description
ABSTRACT: Health care capacity planning is the art and science of predicting the quantity of resources required to deliver health care service at specified levels of cost and quality. Because of variability in the arrival of patients and in the delivery of health care services, successfully meeting the demand for health care services is a daunting task that requires an understanding of the inherent trade-o® between its cost and quality of service. In our work, we model the general health care systems as queueing stations and incorporate queueing theory into an optimization framework. The queueing modeling approach captures the stochastic nature of arrivals and service times that is typical in health care systems. The optimization framework determines the minimum cost capacity required to achieve a target level of customer service. The inclusions of queueing equations and discrete capacity options result the capacity planning models in non-linear integer programming formulations. We develop e®ective solution algorithms to obtain high quality solutions particularly for realistic-sized problems. For the analysis of underlying queuing systems, we either use available results from the literature or develop approximations. For the solution of optimization models, we employ network optimization, meta-heuristic, and Lagrangian relaxation approaches to develop e®ective solution algorithms. We present results from extensive computational experiments to demonstrate the computational e"ciency and e®ectiveness of the proposed solution approaches.
Author: Antonio Sforza Publisher: Springer ISBN: 3319673084 Category : Mathematics Languages : en Pages : 607
Book Description
This proceedings volume highlights the state-of-the-art knowledge related to optimization, decisions science and problem solving methods, as well as their application in industrial and territorial systems. It includes contributions tackling these themes using models and methods based on continuous and discrete optimization, network optimization, simulation and system dynamics, heuristics, metaheuristics, artificial intelligence, analytics, and also multiple-criteria decision making. The number and the increasing size of the problems arising in real life require mathematical models and solution methods adequate to their complexity. There has also been increasing research interest in Big Data and related challenges. These challenges can be recognized in many fields and systems which have a significant impact on our way of living: design, management and control of industrial production of goods and services; transportation planning and traffic management in urban and regional areas; energy production and exploitation; natural resources and environment protection; homeland security and critical infrastructure protection; development of advanced information and communication technologies. The chapters in this book examine how to deal with new and emerging practical problems arising in these different fields through the presented methodologies and their applications. The chapter topics are applicable for researchers and practitioners working in these areas, but also for the operations research community. The contributions were presented during the international conference “Optimization and Decision Science” (ODS2017), held at Hilton Sorrento Palace Conference Center, Sorrento, Italy, September 4 – 7, 2017. ODS 2017, was organized by AIRO, Italian Operations Research Society, in cooperation with DIETI (Department of Electrical Engineering and Information Technology) of University “Federico II” of Naples.
Author: Jingshan Li Publisher: World Scientific Publishing Company ISBN: 9789813220843 Category : Medical Languages : en Pages : 309
Book Description
Sustainability is going to be one of the most important issues of the coming decades. For the first time, institutions at all levels, public and private, national and international, are teaming up to combat climate change and to promote more sustainable s
Author: Brian T. Denton Publisher: Springer Science & Business Media ISBN: 1461458854 Category : Business & Economics Languages : en Pages : 542
Book Description
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.
Author: Yuehwern Yih Publisher: CRC Press ISBN: 1439803625 Category : Medical Languages : en Pages : 798
Book Description
With rapidly rising healthcare costs directly impacting the economy and quality of life, resolving improvement challenges in areas such as safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity has become paramount. Using a system engineering perspective, Handbook of Healthcare Delivery Systems offers theoretical foundation
Author: Adedeji B. Badiru Publisher: CRC Press ISBN: 146651504X Category : Technology & Engineering Languages : en Pages : 1480
Book Description
A new edition of a bestselling industrial and systems engineering reference, Handbook of Industrial and Systems Engineering, Second Edition provides students, researchers, and practitioners with easy access to a wide range of industrial engineering tools and techniques in a concise format. This edition expands the breadth and depth of coverage, emphasizing new systems engineering tools, techniques, and models. See What’s New in the Second Edition: Section covering safety, reliability, and quality Section on operations research, queuing, logistics, and scheduling Expanded appendix to include conversion factors and engineering, systems, and statistical formulae Topics such as control charts, engineering economy, health operational efficiency, healthcare systems, human systems integration, Lean systems, logistics transportation, manufacturing systems, material handling systems, process view of work, and Six Sigma techniques The premise of the handbook remains: to expand the breadth and depth of coverage beyond the traditional handbooks on industrial engineering. The book begins with a general introduction with specific reference to the origin of industrial engineering and the ties to the Industrial Revolution. It covers the fundamentals of industrial engineering and the fundamentals of systems engineering. Building on this foundation, it presents chapters on manufacturing, production systems, and ergonomics, then goes on to discuss economic and financial analysis, management, information engineering, and decision making. Two new sections examine safety, reliability, quality, operations research, queuing, logistics, and scheduling. The book provides an updated collation of the body of knowledge of industrial and systems engineering. The handbook has been substantively expanded from the 36 seminal chapters in the first edition to 56 landmark chapters in the second edition. In addition to the 20 new chapters, 11 of the chapters in the first edition have been updated with new materials. Filling the gap that exists between the traditional and modern practice of industrial and systems engineering, the handbook provides a one-stop resource for teaching, research, and practice.
Author: Pengyi Shi Publisher: ISBN: Category : Communicable diseases Languages : en Pages :
Book Description
Delivering health care services in an efficient and effective way has become a great challenge for many countries due to the aging population worldwide, rising health expenses, and increasingly complex healthcare delivery systems. It is widely recognized that models and analytical tools can aid decision-making at various levels of the healthcare delivery process, especially when decisions have to be made under uncertainty. This thesis employs stochastic models to improve decision-making under uncertainty in two specific healthcare settings: inpatient flow management and infectious disease modeling. In Part I of this thesis, we study patient flow from the emergency department (ED) to hospital inpatient wards. This line of research aims to develop insights into effective inpatient flow management to reduce the waiting time for admission to inpatient wards from the ED. Delayed admission to inpatient wards, also known as ED boarding, has been identified as a key contributor to ED overcrowding and is a big challenge for many hospitals. Part I consists of three main chapters. In Chapter 2 we present an extensive empirical study of the inpatient department at our collaborating hospital. Motivated by this empirical study, in Chapter 3 we develop a high fidelity stochastic processing network model to capture inpatient flow with a focus on the transfer process from the ED to the wards. In Chapter 4 we devise a new analytical framework, two-time-scale analysis, to predict time-dependent performance measures for some simplified versions of our proposed model. We explore both exact Markov chain analysis and diffusion approximations. Part I of the thesis makes contributions in three dimensions. First, we identify several novel features that need to be built into our proposed stochastic network model. With these features, our model is able to capture inpatient flow dynamics at hourly resolution and reproduce the empirical time-dependent performance measures, whereas traditional time-varying queueing models fail to do so. These features include unconventional non-i.i.d. (independently and identically distributed) service times, an overflow mechanism, and allocation delays. Second, our two-time-scale framework overcomes a number of challenges faced by existing analytical methods in analyzing models with these novel features. These challenges include time-varying arrivals and extremely long service times. Third, analyzing the developed stochastic network model generates a set of useful managerial insights, which allow hospital managers to (i) identify strategies to reduce the waiting time and (ii) evaluate the trade-off between the benefit of reducing ED congestion and the cost from implementing certain policies. In particular, we identify early discharge policies that can eliminate the excessively long waiting times for patients requesting beds in the morning. In Part II of the thesis, we model the spread of influenza pandemics with a focus on identifying factors that may lead to multiple waves of outbreak. This line of research aims to provide insights and guidelines to public health officials in pandemic preparedness and response. In Chapter 6 we evaluate the impact of seasonality and viral mutation on the course of an influenza pandemic. In Chapter 7 we evaluate the impact of changes in social mixing patterns, particularly mass gatherings and holiday traveling, on the disease spread. In Chapters 6 and 7 we develop agent-based simulation models to capture disease spread across both time and space, where each agent represents an individual with certain socio-demographic characteristics and mixing patterns. The important contribution of our models is that the viral transmission characteristics and social contact patterns, which determine the scale and velocity of the disease spread, are no longer static. Simulating the developed models, we study the effect of the starting season of a pandemic, timing and degree of viral mutation, and duration and scale of mass gatherings and holiday traveling on the disease spread. We identify possible scenarios under which multiple outbreaks can occur during an influenza pandemic. Our study can help public health officials and other decision-makers predict the entire course of an influenza pandemic based on emerging viral characteristics at the initial stage, determine what data to collect, foresee potential multiple waves of attack, and better prepare response plans and intervention strategies, such as postponing or cancelling public gathering events.
Author: Asli Özen
Author: Asli Özen
Author: Jingshan Li
Author: Chin-I. Lin
Author: Antonio Sforza
Author: Lei Wang
Author: Jingshan Li
Author: Brian T. Denton
Author: Yuehwern Yih
Author: Adedeji B. Badiru
Author: Pengyi Shi