List of Figures and Tables; Preface; Acknowledgments; About the Editors; PART I. SETTING UP FOR EVALUATION; Chapter 1. Introduction; Background: Challenges and Opportunities; Evaluation and Health Care Delivery System Transformation; The Global Context for Considering Evaluation Methods and Evidence-Based Decision Making; Book’s Intent; Chapter 2. Setting the Stage; Typology for Program Evaluation; Planning an Evaluation: How Are the Changes Expected to Occur?; Developing Evaluations: Some Preliminary Methodological Thoughts; Prospectively Planned and Integrated Program Evaluation; Summary; Chapter 3. Measurement and Data; Guiding Principles; Measure Types; Measures of Structure; Measures of Process; Measures of Outcomes; Selecting Appropriate Measures; Data Sources; Looking Ahead; Summary; PART II.
EVALUATION METHODS; Chapter 4. Causality and Real-World Evaluation; Evaluating Program/Policy Effectiveness: The Basics of Inferring Causality; Defining Causality; Assignment Mechanisms; Three Key Treatment Effects; Statistical and Real-World Considerations for Estimating Treatment Effects; Summary; Chapter 5. Randomized Designs; Randomized Controlled Trials; Stratified Randomization; Group Randomized Trials; Randomized Designs for Health Care; Summary; Chapter 6. Quasi-experimental Methods: Propensity Score Techniques; Dealing With Selection Bias; Comparison Group Formation and Propensity Scores; Regression and Regression on the Propensity Score to Estimate Treatment Effects; Summary; Chapter 7.
Quasi-experimental Methods: Regression Modeling and Analysis; Interrupted Time Series Designs; Comparative Interrupted Time Series; Difference-in-Difference Designs; Confounded Designs; Instrument Variables to Estimate Treatment Effects; Regression Discontinuity to Estimate Treatment Effects; Fuzzy Regression Discontinuity Design; Additional Considerations: Dealing With Nonindependent Data; Summary; Chapter 8.
Treatment Effect Variations Among the Treatment Group; Context: Factors Internal to the Organization; Evaluation Approaches and Data Sources to Incorporate Contextual Factors; Context: External Factors That Affect the Delivery or Potential Effectiveness of the Treatment; Individual-Level Factors That May Cause Treatment Effect to Vary; Methods for Examining the Individual Level Heterogeneity of Treatment Effects; Multilevel Factors; Importance of Incorporating Contextual Factors Into an Evaluation; Summary; Chapter 9. The Impact of Organizational Context on Heterogeneity of Outcomes: Lessons for Implementation Science; Context for the Evaluation: Some Examples From Centers for Medicare and Medicaid Innovation; Evaluation for Complex Systems Change; Frameworks for Implementation Research; Organizational Assessment Tools; Analyzing Implementation Characteristics; Summary; PART III.
MAKING EVALUATION MORE RELEVANT TO POLICY; Chapter 10. Evaluation Model Case Study: The Learning System at the Center for Medicare and Medicaid Innovation; Step 1: Establish Clear Aims; Step 2: Develop an Explicit Theory of Change; Step 3: Create the Context Necessary for a Test of the Model; Step 4: Develop the Change Strategy; Step 5: Test the Changes; Step 6: Measure Progress Toward Aim; Step 7: Plan for Spread; Summary; Chapter 11. Program Monitoring: Aligning Decision Making With Evaluation; Nature of Decisions; Cases: Examples of Decisions; Evidence Thresholds for Decision Making in Rapid-Cycle Evaluation; Summary; Chapter 12. Alternative Ways of Analyzing Data in Rapid-Cycle Evaluation; Statistical Process Control Methods; Regression Analysis for Rapid-Cycle Evaluation; A Bayesian Approach to Program Evaluation; Summary; Chapter 13.
Synthesizing Evaluation Findings; Meta-analysis; Meta-evaluation Development for Health Care Demonstrations; Meta-regression Analysis; Bayesian Meta-analysis; Putting It Together; Summary; Chapter 14. Decision Making Using Evaluation Results; Research, Evaluation, and Policymaking; Program/Policy Decision Making Using Evidence: A Conceptual Model; Multiple Alternatives for Decisions; A Research Evidence/Policy Analysis Example: Socioeconomic Status and the Hospital Readmission Reduction Program; Other Policy Factors Considered; Advice for Researchers and Evaluators; Chapter 15.
Communicating Research and Evaluation Results to Policymakers; Suggested Strategies for Addressing Communication Issues; Other Considerations for Tailoring and Presenting Results; Closing Thoughts on Communicating Research Results; Appendix A: The Primer Measure Set; Appendix B: Quasi-experimental Methods That Correct for Selection Bias: Further Comments and Mathematical Derivations; Propensity Score Methods; An Alternative to Propensity Score Methods; Assessing Confoundedness; Using Propensity Scores to Estimate Treatment Effects; Unconfounded Design When Assignment Is at the Group Level; Index;

"Evaluation for Health Policy and Health Care appeals to students, evaluators, and instructors interested cutting-edge health care and health policy evaluation in this era of health care innovation. This core, graduate-level text for the current health care evaluation landscape explores the the best practices and applications for producing, synthesizing, visualizing, using, and disseminating health care evaluation evidence and reports. The text focuses on quantitative, qualitative, and meta-analytic approaches to analysis, providing a guide for both those executing evaluations and those using the data to make policy decisions. Starting with a chapter on evaluation planning, this text walks readers through measurement and causality, key foundations for any evaluations. The text then proceeds in order of research steps, moving from the design and analysis phase with randomized designs, quasi-experimental designs, regression modeling, treatment effects, and implementation science to policy-relevant research techniques, covering program monitoring, alternative methods for rapid-cycle evaluation, meta-analysis, and data-driven decision making. A special chapter on disseminating research findings to policy makers emphasizes this crucial, final step. Pedagogical features like learning objectives, discussion questions, real-world examples, and practice data and code make this easy to use in a classroom setting, while applications and modern methodological approaches make the book useful in evaluation settings. This is the contemporary, applied text on evaluation that your students need".