Comparative Effectiveness Research (CER) Survey Course

This groundbreaking course tackles one of the most opportune and relevant topics in medicine: Comparative Effectiveness Research (CER). Nationally renowned CER experts describe the current state of CER, define CER tools, and explain state-of-the-art CER methodologies in a series of 15 captivating 2-hour lectures. Each lecture has been professionally videotaped and combined with slides and other learning materials to provide interactive presentations.

Click the plus sign to the left of the lecture title to view the learning objectives. To take the lecture select the CME or Non-CME button.

Course Description and CME Requirements

1
Unit 1: Introduction
 Part 1: Comparative Effectiveness Research: Recent History and Role in Healthcare Reform
Part 2: Rationale for CER

After completing this lecture, you will be able to:
  1. Define CER based on standard definitions and the typical activities that it encompasses
  2. Review the motivations, accomplishments, and impediments for CER
  3. Describe how CER is supported in the United States now and how the new Patient-Centered Outcomes Research Institute will support CER
  4. Identify the roles for CTSAs in facilitating and implementing CER
  5. Discuss specific needs, next steps, and the future of CER
  6. Identify the forces shaping national priorities for CER in the United States
  7. Explain the current CER landscape in the United States
  8. Compare and contrast comparative effectiveness and cost-effectiveness research
 Harry P. Selker, MD, MSPH
Peter J. Neumann, ScD
2
Introduction: A Review of Evidence-Based Medicine (EBM) and a Framework for Understanding the CER Agenda

After completing this lecture, you will be able to:
  1. List the principles of Evidence-Based Medicine (EBM)
  2. State how CER extends the principles of EBM
  3. Describe a framework for understanding the CER agenda
  4. Identify the stakeholders of CER
 Thomas W. Concannon, PhD
3
Unit 2: Evidence Generation
 Part 1: Comparative Effectiveness Trials
Part 2: Assessing Pharmacogenetic Information in Clinical Trials

After completing this lecture, you will be able to:
  1. Identify the need for comparative effectiveness trials, even for drug therapies where "proof of efficacy" is already required prior to approval
  2. Explain the differences between pragmatic/effectiveness trials and explanatory/efficacy trials
  3. List the strengths and limitations of pragmatic versus explanatory designs
  4. State the strengths and limitations of various types of outcome measures, including surrogate versus clinical outcomes
  5. Explain the difference between prognostic and predictive genetic markers
  6. Identify the pros and cons of alternative research designs for assessing pharmacogenetic (predictive) effects
  7. Discuss “repurposed” randomized trials for assessing pharmacogenetic effects
  8. Define empirical data
 David M. Kent, MD, MSc
Thomas A. Trikalinos, MD, PhD
4
Personalized Medicine, Heterogeneity of Treatment Effect, and Implications for Comparative Effectiveness

After completing this lecture, you will be able to:
  1. Identify the limitations of applying the overall results of clinical trials to individual patients
  2. Discuss how summary results of individual trials might not even reflect the benefits of typical patients in the trial
  3. Explain how subgroup analyses are prone both to false-positive and false-negative results
  4. Illustrate approaches that might lead to more credible and actionable subgroup results
  5. Express why multidimensional risk models may have advantages over conventional “one-variable-at-a-time” subgroup analysis
  6. Determine some of the limitations of using genetic information as a basis for exploring heterogeneity of treatment effect
 David M. Kent, MD, MSc
5
Retrospective and Observational Comparative Effectiveness Studies

After completing this lecture, you will be able to:
  1. State the limitations of randomized controlled trials
  2. Identify the settings in which observational studies of comparative effectiveness may be particularly helpful to clinicians and policymakers
  3. Explain the methodological challenges in conducting retrospective, observational CER using existing sources of data
  4. Describe model-based and other approaches to reduce the effects of confounding in observational CER
  5. Discuss specific examples of retrospective and observational CER, and how these have informed public policy and healthcare delivery system change
  6. List key aspects and the steps of a systematic review
  7. Identify the methodological and inferential challenges of longitudinal observational studies of health outcomes and delivery system change
 Dana Gelb Safran, ScD
Peter K. Lindenauer MD, MSc
6
Unit 3: Evidence Synthesis
 Systematic Review and Meta-Analysis

After completing this lecture, you will be able to:
  1. List the reasons for conducting systematic reviews
  2. Appreciate the role of systematic review in CER
  3. Describe the components of a systematic review
  4. State the role of analytic frameworks in systematic review and the approach to formulate answerable systematic review questions
  5. Identify the users and producers of systematic reviews
  6. Define the basic principles of combining data
  7. Identify the common metrics for meta-analysis
  8. List the basics of combining results across studies and effects of weights
  9. Explain the meaning of heterogeneity
  10. Discuss the fixed effect and random effects model
  11. Interpret meta-analysis results
 Joseph Lau, MD
Christopher H. Schmid, PhD
7
Unit 4: Evidence Integration
 Decision Modeling – Cost-Effectiveness

After completing this lecture, you will be able to:
  1. Show how the probability of a diagnosis is affected by a test result, sensitivity, and specificity
  2. Describe how evidence can be integrated using decision trees
  3. Illustrate the concept of threshold probabilities and their implications
  4. Discuss how sensitivity analyses are performed and what they mean
  5. Explain how patient preferences (utilities or values) can be integrated into patient-centered choices using decision analysis
  6. Identify different types of economic analyses in comparative effectiveness research
  7. Explain how to calculate incremental cost-effectiveness
  8. List how cost-effectiveness analysis is being used for technology assessment
Stephen G. Pauker, MD
John B. Wong, MD
8
Decision Modeling – Simulations

After completing this lecture, you will be able to:
  1. Explain the principles underlying the use of Markov models, including (a) how to compute the distribution of a cohort among population states given a starting distribution and a set of transition probabilities; (b) how a model can be used to compute incurred costs and accrued quality-adjusted life years over time; and (c) Markov model limitations and how they can be addressed by more complex Markov model designs
  2. Discuss how simulation models can be used to characterize uncertainty attending model assumptions, including use of nonprobabilistic sensitivity analysis and probabilistic uncertainty analysis
  3. Define decision-making contextual factors that make the resolution of uncertainty either more or less valuable
 Joshua T. Cohen, PhD
9
Unit 5: Use of Evidence in Decision Making
 Community Engagement and Input into CER

After completing this lecture, you will be able to:
  1. Define "community" and "community engagement"
  2. Delineate key points where community engagement may enhance comparative effectiveness research
  3. Identify examples of research strategies and methodologies employed to engage communities
 Laurel K. Leslie, MD, MPH
10
Clinical Practice Guidelines

After completing this lecture, you will be able to:
  1. Explain the rationale for clinical practice guidelines
  2. Discuss the process of clinical practice guideline development: (a) evidence synthesis and appraisal; (b) grading of evidence and recommendations
  3. Identify challenges in making clinical practice guidelines more trustworthy: (a) applying transparent judgments when moving from systematic reviews to recommendations; (b) containing conflicts of interest in guideline development committees; and (c) making guidelines applicable to persons with more than one disease
 Katrin Uhlig, MD, MS
11
Clinical Effectiveness Trials and Predictive Instruments as Decision Support for Implementing CER

After completing this lecture, you will be able to:
  1. Discuss the use of comparative effectiveness trials for comparing strategies of care
  2. Explain the use of predictive instruments as decision support for evidence-based clinical care and their evaluation by clinical trials
  3. Review how predictive instruments are incorporated into the use of medications and other treatments
  4. Discuss the possible use of predictive instruments for efficient and ethical conduct of clinical effectiveness trials
 Harry P. Selker, MD, MSPH
12
Drug Development in the CER Era

After completing this lecture, you will be able to:
  1. Assess the economic, regulatory, and political pressures affecting pharmaceutical and biopharmaceutical developers today
  2. Discuss current drug development metrics, including the time, cost, and risk of development
  3. Examine how companies, in response to competitive and economic pressures, are adopting new strategies and practices to improve R&D performance
 Kenneth I. Kaitin, PhD
13
Using Comparative Effectiveness Research to Reach Employers and Employees

After completing this lecture, you will be able to:
  1. Identify current and projected health, healthcare, and cost issues facing employers and employees
  2. List workplace policies, practices, and programs that are being used to address health and cost trends
  3. Describe the evidence base for workplace health programs in wellness, occupational health, and benefits design
  4. Identify methodological problems and solutions to developing the evidence base and the role of comparative effectiveness studies in generating required evidence
  5. Identify issues related to the dissemination and implementation of evidence from comparative effectiveness studies
 Debra J. Lerner, MS, PhD
14
Economic and Policy Implications of CER

After completing this lecture, you will be able to:
  1. Discuss how performance assessment and financial incentive models have been used to impact transformational changes in healthcare policy
  2. Using specific examples, explain how comparative effectiveness research and outcomes measurement impact value-priced purchasing and the cost of healthcare delivery
  3. Describe how a multidimensional framework for measuring outcomes of care and efficiency assists policymakers to make informed decisions that improve health care
  4. Discuss opportunities and roles for use of insurance data to improve health care
  5. Identify the differences between chart-based clinical process-of-care measures versus clinical outcomes measurement and comparative effectiveness research in healthcare delivery systems
 Christopher P. Tompkins, PhD
15
Unit 6: Future Directions in CER
 Part 1: The IOM 100 Priorities and AHRQ 14 Priority Conditions and Populations
Part 2: The USPSTF Breast Cancer Screening Guidelines (Mammography) and CER: A Panel Discussion

After completing this lecture, you will be able to:
  1. Describe the priority-setting processes for CER-related funds, as established by the Affordable Care Act
  2. Identify IOM priorities related to their individual research interests
  3. Distinguish CER studies aimed at comparison of clinical interventions from those that compare effective healthcare strategies, or both clinical interventions and healthcare strategies
 Thomas W. Concannon, PhD
Harry P. Selker, MD, MSPH
Faculty Panel

The website was supported by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 RR025752. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.