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Evaluation for Health Policy and Health Care
A Contemporary Data-Driven Approach
Edited by:
- Steven Sheingold - Department of Health and Human Services, USA
- Anupa Bir - RTI International, USA
Additional resources:
September 2019 | 336 pages | SAGE Publications, Inc
This is the contemporary, applied text on evaluation that your students need.
Evaluation for Health Policy and Health Care: A Contemporary Data-Driven Approach explores the best practices and applications for producing, synthesizing, visualizing, using, and disseminating health care evaluation research and reports. This graduate-level text will appeal to those interested in cutting-edge health program and health policy evaluation in this era of health care innovation. Editors Steven Sheingold and Anupa Bir’s core 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. It is designed to provide real-world applications within health policy to make learning more accessible and relevant, and to highlight the remaining challenges for using evidence to develop policy.
Evaluation for Health Policy and Health Care: A Contemporary Data-Driven Approach explores the best practices and applications for producing, synthesizing, visualizing, using, and disseminating health care evaluation research and reports. This graduate-level text will appeal to those interested in cutting-edge health program and health policy evaluation in this era of health care innovation. Editors Steven Sheingold and Anupa Bir’s core 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. It is designed to provide real-world applications within health policy to make learning more accessible and relevant, and to highlight the remaining challenges for using evidence to develop policy.
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 Unconfoundedness |
| Using Propensity Scores to Estimate Treatment Effects |
| Unconfounded Design When Assignment Is at the Group Level |
Index
Supplements
Instructor Resource Site
study.sagepub.com/sheingold1e
Password-protected Instructor Resources include the following:
Password-protected Instructor Resources include the following:
- Editable, chapter-specific Microsoft® PowerPoint® slides offer you complete flexibility in easily creating a multimedia presentation for your course.
- Lecture Notes, including Outline and Objectives, which may be used for lecture and/or student handouts.
- Case studies from SAGE Research Methods accompanied by critical thinking/discussion questions.
- Tables and figures from the printed book are available in an easily-downloadable format for use in papers, hand-outs, and presentations.
Student Study Site
Open-access Student Resources include case studies from SAGE Research Methods accompanied by critical thinking/discussion questions.
Open-access Student Resources include case studies from SAGE Research Methods accompanied by critical thinking/discussion questions.
“This text offers a general introduction to the process and methods used to conduct rigorous and timely evaluations of health policies and programs using real-world examples. It would make an excellent text for a program evaluation course.”
University of Iowa
“A must read for anyone interested in monitoring and evaluation! The text does a great job addressing the important ingredients for a successful evaluation.”
Barry University
“Evaluating health policies and programs can be a very challenging process because the evaluation itself is so often an afterthought, leading to a variety of data issues that can produce biased results and poor policy decisions. This book provides an outstanding–yet highly accessible–overview of a wide variety of methods that evaluators can use to minimize these biases and generate robust evidence for decision-makers.”
University of Alabama at Birmingham
