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I. Introduction -- 1. Introducing Decision Making in a World of Comparative Effectiveness Research -- 2. Perspectives on Decision Making in a World of Comparative Effectiveness: Views from Diverse Constituencies -- II. The Future of CER for Evidence Developers: Perspectives from Pharmaceutical Decision Makers -- 3. Perspectives on the Use of CER by Life Sciences Executives: An Interview with Mike Bonney -- 4. Perspectives on the Use of CER by Life Sciences Executives: An Interview with a Senior Executive at an International Life Science Company -- 5. CER: A Pharmaceutical Industry Perspective on Outlook, Dilemmas, and Controversies -- 6. Impact of Comparative Effectiveness Research on Drug Development Strategy and Innovation -- 7. Pricing of Pharmaceuticals: Current Trends and Outlook, and the Role of CER -- III. Evolving Stakeholder Considerations: Patients, Physicians, Regulators and Payers -- 8. Are Real-World Data and Evidence Good Enough to Inform Healthcare and Health Policy Decision Making? -- 9. Translating CER Evidence to Real-World Decision-Making: Some Practical Considerations -- 10. Decision Making by Public Payers -- 11. Patient and Stakeholder Engagement in Designing Pragmatic Clinical Trials -- 12. Policy Considerations: Ex-U.S. Payers and Regulators -- 13. Perspectives on the Common Drug Review (CDR) Process at the Canadian Agency for Drugs and Technologies in Health (CADTH) -- 14. Evaluating Non-Pharmaceutical Technologies at the Canadian Agency for Drugs and Technologies in Health (CADTH) -- 15. Challenges and Opportunities in the Dissemination of CER Information to Physicians and Payers: A Legal Perspective -- 16. Legal Considerations in a World of CER -- IV. Emerging Challenges, Methods and Applications of CER: Real-world and Big Data -- 17. Application of CER to Promote Adherence to Clinical Practice Guidelines -- 18. Challenges in Developing and Assessing CER for Medical Technology -- 19. Evidence Generation Using Big Data: Challenges and Opportunities -- 20. Indirect Comparisons Using Clinical Trial Data: 5 Years Later -- 21. Decision-Making with Machine Learning in Our Modern, Data-Rich Healthcare Industry.

In the past decade there has been a worldwide evolution in evidence-based medicine that focuses on real-world Comparative Effectiveness Research (CER) to compare the effects of one medical treatment versus another in real world settings. While most of this burgeoning literature has focused on research findings, data and methods, Howard Birnbaum and Paul Greenberg (both of Analysis Group) have edited a book that provides a practical guide to decision making using the results of analysis and interpretation of CER. Decision Making in a World of Comparative Effectiveness contains chapters by senior industry executives, key opinion leaders, accomplished researchers, and leading attorneys involved in resolving disputes in the life sciences industry. The book is aimed at 'users' and 'decision makers' involved in the life sciences industry rather than those doing the actual research. This book appeals to those who commission CER within the life sciences industry (pharmaceutical, biologic, and device manufactures), government (both public and private payers), as well as decision makers of all levels, both in the US and globally.