Considerations for Developing Applied Health Policy Models: The Example of HIV Treatment Expansion in Resource-Limited Settings -- Cost-effectiveness Analysis Using Registry and Administrative Data -- Public Health Modeling at the Centers for Disease Control and Prevention -- OR in Public Health: A Little Help Can Go a Long Way -- Review of Operations Research Tools and Techniques Used for Influenza Pandemic Planning -- Analytical Long-Term Care Capacity Planning -- Managing Community-based Care for Chronic Diseases: The Quantitative Approach -- Project Management Approach to Implement Clinical Pathways: An Example for Thyroidectomy -- EMS Planning and Management -- Impact of In-patient Reimbursement Systems on Hospital Performance: The Austrian Case-based Payment Strategy -- Assessing Prevention for Positives: Cost-Utility Assessment of Behavioral Interventions for Reducing HIV Transmission -- Modeling the Impact of New HIV Prevention Techniques in Sub-Saharan Africa -- REACH: A Practical HIV Resource Allocation Tool for Decision Makers -- Active Vaccine and Drug Surveillance Towards a 100 Million Member System -- Application of Operations Research to Funding Decisions for Treatments with Rare Disease -- Modeling Risk Sharing Agreements and Patient Access Schemes -- Evaluating Health Care Policy Decisions: Canadian Blood Services in Atlantic Canada -- Improving the Efficiency of Cost-effective Analysis to Inform Policy Decisions in the Real World: Lessons from the Pharmacoeconomics Research Unit at Cancer Care Ontario.

Operations research tools are ideally suited to providing solutions and insights for the many problems health policy-maker's face. Indeed, a growing body of literature on health policy analysis, based on operations research methods, has emerged to address the problems mentioned above and several others. The research in this field is often multi-disciplinary, being conducted by teams that include not only operations researchers but also clinicians, economists and policy analysts. The research is also often very applied, focusing on a specific question driven by a decision-maker and many times yielding a tool to assist in future decisions. The goal of this volume was to bring together a group of papers by leading experts that could showcase the current state of the field of operations research applied to health-care policy. There are 18 chapters that illustrate the breadth of this field. The chapters use a variety of techniques, including classical operations research tools, such as optimization, queuing theory, and discrete event simulation, as well as statistics, epidemic models and decision-analytic models. The book spans the field and includes work that ranges from highly conceptual to highly applied. An example of the former is the chapter by Kimmel and Schackman on building policy models, and an example of the latter is the chapter by Coyle and colleagues on developing a Markov model for use by an organization in Ontario that makes recommendations about the funding of new drugs. The book also includes a mix of review chapters, such as the chapter by Hutton on public health response to influenza outbreaks, and original research, such as the paper by Blake and colleagues analyzing a decision by Canadian Blood Services to consolidate services.  This volume could provide an excellent introduction to the field of operations research applied to health-care policy, and it could also serve as an introduction to new areas for researchers already familiar with the topic. The book is divided into six sections. The first section contains two chapters that describe several different applications of operations research in health policy and provide an excellent overview of the field. Sections 2 to 4 present policy models in three focused areas.  Section 5 contains two chapters on conceptualizing and building policy models. The book concludes in Section 6 with two chapters describing work that was done with policy-makers and presenting insights gained from working directly with policy-makers.