Boris Sobolev – författare

In health care systems that provide universal access to care, efforts to contain costs for standby hospital capacity usually result in wait lists for surgical procedures. When access to health care is rationed by such wait lists, the length of time that patients are required to wait is usually uncertain. This uncertainty is a natural product of stochastic variation in service time and in the percentage of urgent cases in any queuing system. However, in a queue for elective (nonemergency) procedures, waiting-time uncertainty has many additionalcauses. Forinstance,decisionsofbothpatientsandcareprovidersmayoverrideaqueuediscipline. Alternatively, the lack of a hospital resource, such as beds in the intensive care unit, may change queuing practices in favor of services that would not require the resource. Waiting time is often compared between regions, hospitals, periods, or surgical services to evaluate p- icy and performance. However, surprisingly little attention has been given to the variation in times spent in a single queue. Why some patients wait longer than others remains an important question in health services - search. Itisunclear,forexample, whether timetoservicevariesmorethanwouldbeexpected throughchance alone after differences in clinical condition are taken into account. Another important issue is preferential allocation of hospital resources. It also remains unclear whether patients of low priority are admitted directly as a way to circumvent long wait lists or to substitute for cancellations on the operating room schedule.

In health care systems that provide universal access to care, efforts to contain costs for standby hospital capacity usually result in wait lists for surgical procedures. When access to health care is rationed by such wait lists, the length of time that patients are required to wait is usually uncertain. This uncertainty is a natural product of stochastic variation in service time and in the percentage of urgent cases in any queuing system. However, in a queue for elective (nonemergency) procedures, waiting-time uncertainty has many additionalcauses. Forinstance,decisionsofbothpatientsandcareprovidersmayoverrideaqueuediscipline. Alternatively, the lack of a hospital resource, such as beds in the intensive care unit, may change queuing practices in favor of services that would not require the resource. Waiting time is often compared between regions, hospitals, periods, or surgical services to evaluate p- icy and performance. However, surprisingly little attention has been given to the variation in times spent in a single queue. Why some patients wait longer than others remains an important question in health services - search. Itisunclear,forexample, whether timetoservicevariesmorethanwouldbeexpected throughchance alone after differences in clinical condition are taken into account. Another important issue is preferential allocation of hospital resources. It also remains unclear whether patients of low priority are admitted directly as a way to circumvent long wait lists or to substitute for cancellations on the operating room schedule.

In health care systems that provide universal access to care, efforts to contain costs for standby hospital capacity usually result in wait lists for surgical procedures. When access to health care is rationed by such wait lists, the length of time that patients are required to wait is usually uncertain. This uncertainty is a natural product of stochastic variation in service time and in the percentage of urgent cases in any queuing system. However, in a queue for elective (nonemergency) procedures, waiting-time uncertainty has many additionalcauses. Forinstance,decisionsofbothpatientsandcareprovidersmayoverrideaqueuediscipline. Alternatively, the lack of a hospital resource, such as beds in the intensive care unit, may change queuing practices in favor of services that would not require the resource. Waiting time is often compared between regions, hospitals, periods, or surgical services to evaluate p- icy and performance. However, surprisingly little attention has been given to the variation in times spent in a single queue. Why some patients wait longer than others remains an important question in health services - search. Itisunclear,forexample, whether timetoservicevariesmorethanwouldbeexpected throughchance alone after differences in clinical condition are taken into account. Another important issue is preferential allocation of hospital resources. It also remains unclear whether patients of low priority are admitted directly as a way to circumvent long wait lists or to substitute for cancellations on the operating room schedule.

The purpose of this book is to place computer simulation studies within the paradigm of intervention research that is concerned with comparing the outcomes of health care delivered under different policies. This book presents computer simulation as a tool for testing various policy alternatives that have been developed by decision-makers within health care systems. This approach differs from the use of computer simulation in operations research, where simulation helps determine the configurations of a system that will allow it to function optimally.  Although simulation of health care processes is not new, few health care systems have used simulations as a basis for re-engineering the delivery of health services. There is growing appreciation that the complexity of health care processes exceeds the capacity of individual disciplines–health services research, health economics, or operations research–to guide health care reform. In this book, the authors focus on bringing the methodological rigor of evaluative research to the design and analysis of such simulation studies. The book is intended as a reference for health services researchers. It offers a comprehensive description of the methodology of conducting simulation studies in evaluation of service alternatives in surgical care using discrete-event models, including the steps for identifying the clinical and managerial activities of the perioperative process, determining the model requirements, implementing simulation models, designing simulation experiments and analyzing the experimental data, and interpreting and reporting results. The book also offers examples of specific aspects of conducting simulation experiments: how to determine the number of runs needed to estimate the effect of implementing a health care policy; how to allocate the number of runs to study groups in simulation experiments aiming to evaluate policy or management alternatives; and how to use statistical analysis toestimate, interpret, and report effect sizes.

The second volume in the Health Services Research series provides a series of perspectives on comparative effectiveness research. Motivated by concern from the general public, governments in virtually all countries with developed and rapidly developing economies have been actively seeking and promoting ways of improving the patient experience of health care, improving the health of populations, and reducing the per capita cost of health care. While comparing treatment outcomes is not a new concept, appreciation of its potential application has grown in recent years. In addition to traditional health sciences methods, modern approaches to comparative effectiveness research now include greater emphasis on social sciences frameworks such as economics, ethics, and implementation science. Moreover, a key feature of the modern approach to comparing treatment outcomes is a focus on the individual patient through explicit consideration of inter-patient variability and patient-reported outcomes.  Comparative Effectiveness Research presents a series of chapters of relevance including introductions to areas that are being incorporated when comparing treatments, country-specific applications, patient-centred approaches, and modern methods. Included are chapters on the following areas that are being considered in treatment comparisons: ethics, economics and costs, implementation science, modern payment schemes (coverage with evidence development), and priority setting. Country-specific examples include an overview chapter on national approaches from various countries in Europe, Australia, and Canada, as well as specific chapters on comparative effectiveness research in Brazil and in the United States. The focus on the individual patient is described through chapters on patient-centred comparative effectiveness research, individualized treatment, the link with personalized medicine, and incorporating patient and public inputfor treatment. Methodological chapters include overviews of data sources, study designs, new statistical methods of combining results, the link with evidence-based medicine, specific issues when comparing drug and non-drug technologies, and dissemination of results.

The purpose of this book is to place computer simulation studies within the paradigm of intervention research that is concerned with comparing the outcomes of health care delivered under different policies. This book presents computer simulation as a tool for testing various policy alternatives that have been developed by decision-makers within health care systems. This approach differs from the use of computer simulation in operations research, where simulation helps determine the configurations of a system that will allow it to function optimally.  Although simulation of health care processes is not new, few health care systems have used simulations as a basis for re-engineering the delivery of health services. There is growing appreciation that the complexity of health care processes exceeds the capacity of individual disciplines–health services research, health economics, or operations research–to guide health care reform. In this book, the authors focus on bringing the methodological rigor of evaluative research to the design and analysis of such simulation studies. The book is intended as a reference for health services researchers. It offers a comprehensive description of the methodology of conducting simulation studies in evaluation of service alternatives in surgical care using discrete-event models, including the steps for identifying the clinical and managerial activities of the perioperative process, determining the model requirements, implementing simulation models, designing simulation experiments and analyzing the experimental data, and interpreting and reporting results. The book also offers examples of specific aspects of conducting simulation experiments: how to determine the number of runs needed to estimate the effect of implementing a health care policy; how to allocate the number of runs to study groups in simulation experiments aiming to evaluate policy or management alternatives; and how to use statistical analysis toestimate, interpret, and report effect sizes.

The Handbook of Health Services Research is a reference for all aspects of the field of health services and outcomes research. It addresses the increasing need for comprehensive, yet balanced, information in a field that welcomes various disciplines: medicine, public health, statistics, economics, management, policy, and information technology. This well-organized reference is an indispensable source of information for everyone who seeks to develop understanding of health systems and to learn about historical, political, and socioeconomic factors that influence health policies at the global, national, regional and local level. Specifically, the Handbook helps readers: Recognize core concepts of health services and outcomes research, such as, need, access, equity, quality and safety; Become familiar with social, political, organizational, behavioral and economic theories that have influenced health systems designs; Learn about frameworks developed for evaluating the organization, financing, delivery, utilization and outcomes of health services; Get an introduction to methods of comparative effectiveness research, program evaluation, health technology assessment and health economics; Identify types and sources of data appropriate for generating valid and reliable information about the delivery of health services; Learn about strengths and weaknesses of various research designs used to study health services and policy issues. The online version of the Handbook of Health Services Research is in the format of a dynamically updated knowledge base, offering search tools, cross-referencing across chapters and linking to supplement data, other major reference works and external articles. The Handbook of Health Services Research is accessible at the level of graduate students even if it is not their focus area. This includes students with various backgrounds: medicine, public health, statistics, economics, management or information technology.