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Fundamentals of Implementation Science Syllabus

Course Learning Objectives

This course explores the current literature on implementation science; introduces strategies for using innovative scientific methods and tools of diverse disciplines to understand and overcome impediments to implementation and facilitate scale-up; and uses applied case studies to identify and contextualize implementation successes and failures. At the end of this course the student should be able to:

  • Identify the major factors that limit the translation of high-quality evidence into effective health programs and describe the role of complementary implementation science research methods in the development of evidence-based health programs and policies.
  • Explain appropriate research and evaluation methods to overcome impediments to implementation and facilitate timely scale-up of proven interventions with high levels of fidelity and effectiveness.
  • Contextualize and explain real-world examples where sound interventions failed or succeeded.
  • Describe at least one framework for designing successful implementation strategies and apply the framework to a real-world health problem.

Module Learning Objectives

Module 1: Introduction to Implementation Science (IS) and IS Data Sources

  • Describe why implementation science is important to global health.
  • Summarize a framework for using implementation science to facilitate the translation of knowledge to successful program implementation.
  • Recognize the value of core systems of information collection to monitor disease and health programs.
  • Identify barriers to implementing robust health information systems.

Module 2: Impact Evaluation and IS Study Designs

  • Describe common impact evaluation methods and study designs used to evaluate the effects of programs at scale.
  • Distinguish between internal validity and external validity, and describe the importance of external validity within implementation science.
  • Recognize the importance of impact evaluations in the design of public health policies.

Module 3: Economic Evaluation

  • Provide an overview of different economic evaluation methods.
  • Provide an overview of how to conduct a cost-effectiveness evaluation.

Module 4: Qualitative Health System Research

  • Identify qualitative data collection methods and sampling approaches, and describe their implications for analysis and interpretation of data in implementation science studies.
  • Identify how qualitative research design and methods can be developed to maximize rigor, validity, and reliability of findings in implementation studies.
  • Describe the benefits and limitations of mixing qualitative and quantitative methods in operational and implementation science study designs.

Module 5: Organizational Readiness

  • Explain the theory behind and importance of organizational readiness.

Module 6: Quality Improvement as a Management Tool

  • Define Plan – Do –Study – Act cycles and how they can be used in continuous quality improvement.
  • Demonstrate how quality improvement can be used to facilitate broad scale-up of health programs.

Module 7: Stakeholder and Policy Analysis

  • Describe the stages of policy development and how empirical information can be used at each stage.
  • Identify and map key stakeholders in a policy issue.

Module 8: Dissemination Research

  • Familiarize yourself with implementation science frameworks for dissemination of evidence-based health promotion practices.
  • Discuss the need for dissemination research and describe the roles that researchers play in dissemination.

Module 9: Social Marketing of Implementation Strategies

  • Explain the process of developing an effective social marketing strategy.
  • Assess the incremental value of social marketing strategies in health program development and execution.

Module 10: Operations Research as a Contributing Discipline

  • Identify basic lean implementation and its application to healthcare settings: waste and time, value steam mapping, process improvement/Kaizen.
  • Recognize other potential applications of modeling for operations research.
  • Identify appropriate implementation science methods and strategies to develop and implement successful, large-scale public health programs.