Online Courses

Course Modules Title Category #1 Category #2 Instructor Description
CTSA Readings Recommended Readings        

CTSA Online 1


Lesson 1: Course Introduction General   Joy Melnikow, MD, MPH Course Overview, CER Background

CTSA Online 2


Lesson 2: History and Basic Elements of Randomized Clinical Trials Experimental   Daniel J. Tancredi, PhD Clinical Trials, Confounding in Design, Key advantages of Randomization, Blinding (Masking), A Landmark RCT, etc, no outline and is a mixed history of RCT's.

CTSA Online 3


Lesson 3: Explanatory and Pragmatic Trials for CER Experimental General Richard L. Kravitz, MD, MSPH Examine clinical trials within the context of the varied research approaches used in comparative effectiveness research and other forms of clinical research.

CTSA Online 4


Lesson 4: Evidence-Based Medicine, Heterogeneity of Treatment Effects, and the Trouble with Averages Evidence General Richard L. Kravitz, MD, MSPH Fundamental contradiction of evidence based medicine: Non-uniform treatment effects, EBM estimates for average patients, not individual patients.

CTSA Online 5


Lesson 5: Outcomes Assessment in Clinical Trials General   Richard L. Kravitz, MD, MSPH Outcomes in context of CER, Taxonomy of outcomes, Surrogate outcomes, Composite outcomes.

CTSA Online 6


Lesson 6: Analyzing Data From Randomized Clinical Trials General Experimental Daniel J. Tancredi, PhD Analysis of Data from large scale phase 3 trials, Essential features of analyses, Review good clinical practices concerning data analysis

CTSA Online 7


Lesson 7: Clinical Trials Data Infrastructure, Management, and Reporting General Experimental Daniel J. Tancredi, PhD Best practices, Trial policies and practices, Clinical Trials Methods

Module 2 Overview


Module 2 Overview General Observational Patrick Romano, MD MPH 6 defining characteristics of CER, Introduction of Guest Speakers, Observational Studies

CTSA Online 8


Lesson 8: Using the UC Davis Cohort Discovery Tool, Powered by i2b2, to Facilitate CER General   Este Geraghty, MD, MS, MPH, FASCP What is the UCD Cohort Discovery Tool?, Queries using the CDT, Live Demo, Where to get training

CTSA Online 9


Lesson 9: Use of Observational Data in CER, Use of OSHPD Administrative Data Observational   Richard H. White MD Use of observational data in performing CER, Use of Administrative Data from OSHPD

CTSA Online 10


Lesson 10: Computer-Aided Detection and Screening Mammography Observational General Joshua J. Fenton, MD, MPH Brief background about CAD technology, Observational Study from 2007 New England Journal of Medicine, How data infrastructures also support CER

CTSA Online 11


Lesson 11: Off-Pump vs. On-Pump Bypass Surgery General   Zhongmin Li, PhD Comparison of outcomes dealing with stroke for Off Pump vs. On Pump Bypass Surgery

CTSA Online 12


Lesson 12: Using National HCUP Data to Evaluate CE of Pediatric Empyema Treatments General   Su-Ting T. Li, MD, MPH No Outline, Presentation of effectiveness of Empyema Treatments

CTSA Online 13


Lesson 13: Managing Dependent & Independent Variables in Observational CER Studies Observational General Peter Franks and Patrick Romano MD, MPH Dependent and Independent variables in observational studies, Helpful tricks to develop analytic plan

CTSA Online 14


Lesson 14: Observational Studies for CER – How can they be made as good as RCT's General   Patrick Romano, MD MPH Role of Missing Data, How can missing data be minimized, Statistical Techniques to compensate for problems caused by missing data

CTSA Online 15


Lesson 15: Instrumental Variables and Propensity Scores Observational   Patrick Romano, MD MPH Where is the confounding, Can it be removed or worked around?

CTSA Online 16


Lesson 16: Systematic Review and Meta-analysis- Steps 1-4 Evidence General Tonya Fancher, MD MPH Formulating the Problem and Framing the Question, Searching the Literature, Gathering Information, Evaluating the Quality of Studies

CTSA Online 17


Lesson 17: Pub Med Search Demo     Bruce Abbot Presentation Appears to be Broken

CTSA Online 18


Lesson 18: Analyzing, Interpreting and Presenting the Results of a Systematic Review General Evidence Joy Melnikow, MD, MPH Analyzie and integrate the outcomes of the studies, Involving statisticians with expertise in meta-analysis

CTSA Online 19


Lesson 19: Rules For Economic Efficiency General   Paul Leigh Health Production Function, Concave Downward Curve, Total Product, Marginal Product, Slope, Rule

CTSA Online 20


Lesson 20: Approaches to Cost-effectiveness Modeling Decision   Joy Melnikow, MD, MPH Overview of components involved in cost-effectiveness model, Review of sensitivity analysis

CTSA Online 21


Lesson 21: Estimating Health-Related Quality of Life for CEA General   Joy Melnikow, MD, MPH Health-related Quality of life, Direct Measurements, Indirect Measurements, Choice of measurement

CTSA Online 22


Lesson 22: Comparative Effectiveness Research in Health Policy Formulation General   Joy Melnikow, MD, MPH International Perspectives of CER, Review U.S. Examples, Identify QALY's, ICER's and Concerns with those measures.

OSU Online 1


Causality, Effect Identification & Statistical Inference Observational   J. Michael Oakes, PhD Causation and Counterfactuals, Effect Identification, Statistical Inference

OSU Online 2


Research Design in Comparative Effectiveness Research Experimental Observational J. Michael Oakes, PhD Experimental Designs, Observational Designs

OSU Online 3


Propensity Score Theory Observational   J. Michael Oakes, PhD Confounding, Multiple Regression, Propensity Score Methods

OSU Online 4


Propensity Score Application Observational General J. Michael Oakes, PhD ATE, ACE, ATT, TOT, A Typical Analysis, Propensity Score Methods, Issues and Assumptions

OSU Online 5


Instrumental Variable Methods Observational General J. Michael Oakes, PhD The Problem, IV Model Intuition, Examples, LATE, Worked Example

OSU Online 6


Introduction to Economic Evaluation Decision   Sean D. Sullivan, BscPharm, Msc, PhD Cost and Outcomes Evaluation, Important Types of Economic Analysis, Nature of Economic Assessments, Outcomes for Economic Evaluation, Willingness to Pay for Health Gain

OSU Online 7


Decision Modeling Decision   David L. Veenstra, PhD Errors in Decision Making, Framing a Study, How to Perform Decision Analysis, Sensitivity Analysis, Model Validation, Software

OSU Online 8


Working with Health Care Claims and Complex Survey Data Observational General Brook Martin, PhD. M.P. H Claims and Complex Survey Data, Sources of Data, Stata commands

OSU Online 9


Simple Linear Regression General   Brook Martin, PhD. M.P. H Framework for choosing an analysis, Introduction to Descriptive Analysis of Continuous Data, Applied Introduction Regression Models

OSU Online 10


Survival Analysis General   Brook Martin, PhD. M.P. H Descriptive Analysis of Survival Data, Cox-Proportional Hazard Regression Models

OSU Online 11


An Introduction to Systematic Reviews Evidence General Susan L. Norris, MD, MPH, MS Forming an Answerable Question, Searching for Evidence, Risk of Bias in Primary Studies, Evidence Thesis, Strength of Evidence

OSU Online 12


An Introduction to Meta-Analysis General Evidence Susan L. Norris, MD, MPH, MS Models for Combining Data, Assessing and Exploring Heterogeneity, Publication Bias, Reading and Interpreting Meta-Analyses

OSU Online 13


Translating CER Evidence into Practice, Policy, and Public Health Evidence General Henry Lee, MD, Ralph Gonzales, MD, MSPH Conceptual Framework for Translation, Making the Case for Translation, Selecting Evidence, Measuring Quality and its Determinants, Quality Gap, Outcome Gap, Making Change Happen

OSU Online 14


Translational Toolbox Decision General Ralph Gonzales, MD, MSPH, Henry Lee, MD Classifying Tools, Exemplars: Patients (Decision Support) Clinicians (Practice Guidelines) and Community (CBPR)

OSU Online 15


Pragmatic Clinical Trials 1 Experimental   Christopher Granger, M.D., John P. Vavalle, MD Theraputic Principals, Understanding Treatment Effects, Current State of Clinical Trials, Randomized Studies RCT, Registry Studies, Barriers to RCT

OSU Online 16


Pragmatic Clinical Trials 2 Experimental   Christopher Granger, M.D., John P. Vavalle, MD Importance of Large Clinical Trials, Need for Evidence From Randomized Studies, Limitations with Current Large Clinical Trials, Possible Solutions to Current Limitations and the Role for Pragmatic Clinical Trials, Opportunities for Improving Efficiencies in Clinical Trials, Doing More With Less, The Realities of the Current Funding Structure, Examples of Successful Pragmatic Trials

OSU Summer 17


Introduction to CER Using Observational Data General   Paul L. Hebert, PhD Treatments Considered in CER, Outcomes Assesment in CER, Challenges for CER for Patients with Multiple Chronic Conditions, Challenge of CER using CMS Data, Illustration of a CER Study.

OSU Summer 18


Rubin's Potential Outcome Framework Experimental Observational Paul L. Hebert, PhD Randomized Controlled Trials, OLS Regression, Propensity Matching, Instrumental Variables

OSU Summer 19


Can Quasi-Experiments Yield Causal Inferences Experimental   Matthew L. Maciejewski, PhD Reasons RCT is Gold Standard, Context for Perceived Inferiority of Quasi-Experiments, Differences in Samples for RCT's and Quasi-Experiments, Re-appraising the Value of Quasi-Experiments, Propensity Score Modeling, Conditions Under Which Quasi-Experiments Match RCT Results,

OSU Summer 20


Study Designs Appropriate for Comparative Effectiveness Research Experimental General Matthew L. Maciejewski, PhD Incident vs. Prevalent User Cohorts, Counterfactuals, Understand Definition of and Threats to Internal Validity and External Validity, Appreciate Most Rigorous Quasi-Experimental Study Designs

OSU Summer 21


Defining the Treatment General   Paul L. Hebert, PhD Challenges in Defining the Treatment, where to find data on treatments in observational data, challenges in identifying the treatment

OSU Summer 22


Does X Really Cause Y? Observational   Matthew L. Maciejewski, PhD Can true causal mechanisms ever be established, Treatment vs. Selection

OSU Summer 23


Risk Adjustment Observational General Paul L. Hebert, PhD Measuring Covariates, Demographis, Socio-Demographics, Comorbidity, Severity

OSU Summer 24


Propensity Score Analysis for CER Observational   Matthew L. Maciejewski, PhD Illustrate challenge of causal inference in quasi-experiments, outline general principals and steps in propensity score modeling, Discuss trade offs in different approaches, Illustrate propensity score excecution with worked example, Interpretation with results differ by method

OSU Summer 25


Missing Data General   Paul L. Hebert, PhD Types of missing data, missing data mechanisms, solutions to the missing data problem, paper by engels

OSU Summer 26


Putting It All Together in a CER Analysis Observational General Paul L. Hebert, PhD Illustrate Study Design, outcomes, covariates and methods principles in CER using Medicare Data, Set Up Problem, Present Preliminary results

OSU Summer 27


Instrumental Variable Exercise Observational   Paul L. Hebert, PhD Creating a Geographic Based Instrument, Testing the correlation with treatment, test the correlation with observed confounders,Getting the IV estimate.

OSU Summer 28


Unobserved Confounding Part 1 Observational   Paul L. Hebert, PhD Causes of selection bias in observational CER, Methods for dealing with selction bias

OSU Summer 29


Unobserved Confounding Part 2 Observational   Paul L. Hebert, PhD Causes of selection bias in observational CER, Methods for dealing with selction bias

OSU Summer 30


Unobserved Confounding Part 3 Observational   Paul L. Hebert, PhD Causes of selection bias in observational CER, Methods for dealing with selction bias

OSU Summer 31


Unobserved Confounding Part 4 Observational   sean D. Sullivan, BscPharm, Msc, PhD Causes of selection bias in observational CER, Methods for dealing with selction bias



Comparative Effectiveness Research: Recent History and Role in Healthcare Reform General   Harry P. Selker, MD, MSPH What is CER, What does it do, Making CER Happen, CER roles for CTSA's, Integration of CER into routine clinical care.



A Review of Evidence Based Medicine and a Framework for Understanding the CER Agenda Evidence Stakeholder Thomas W. Concannon, PhD Principles of EBM, How CER extends principles of EBM, Describe a framework for understanding the CER agenda, Identify the stakeholders of CER



Comparative Effectiveness Trials Experimental General David M. Kent, MD, Msc Need for Comparative Effectiveness Trials, differences between pragmatic/effectiveness trials and explanatory efficacy trials, strengths and limitations of pragmatic vs. explanatory designs, state the strengths and limitations of various types of outcome measures including surrogates clinical outcomes



Personalized Medicine, Heterogeneity of Treatment Effect, and Implications for Comparative Effectiveness Experimental General David M. Kent, MD, Msc Identify the limitations of applying the overall results of clinical trials to individual patients, Discuss how summary results of individual trials might not even reflect the benefits of typical patients in the trial, Explain how subgroup analyses are prone both to false-positive and false negative results, Illustrate approaches that might lead to more credible and actionable subgroup results, Express why Multidimensional risk models may have advantages over conventional “one-variable-at-a-time” subgroup analysis, Determine some of the limitations of using genetic information as a basis for exploring heterogeneity of treatment effect



Observational Methods in Comparative Effectiveness Research Observational Experimental Peter K. Lindenauer, MD, Msc Review the limitations of RCTs and the settings in which observational CER may be helpful to clinicians and policymakers, Explain the methodological challenges in conducting observational CER using existing/secondary sources of data, Describe model-based and other approaches to reduce the effects of confounding in observational CER



Systematic Review Evidence   Joseph Lau, MD List the reasons for conducting systematic reviews, Appreciate the role of systematic review in CER, Describe the components of a systematic review, State the role of analytic frameworks in systematic review and the approach to formulate answerable systematic review questions, Identify the users and producers of systematic reviews



Decision Analysis Decision General Stephen G. Pauker, MD, MACP Show how the probability of a diagnosis is affected by a test result, sensitivity, and specificity, Describe how evidence can be integrated using decision trees, Illustrate the concept of threshold probabilities and their implications, Discuss how sensitivity analyses are performed and what they mean, Explain how patient preferences can be integrated into patient-centered choices using decision analysis.



Simulation Models and Value of Information Analysis Decision   Joshua T. Cohen, PhD Explain the use of simulation models to characterize disease history and outcomes, Discuss quantifying simulation model uncertainty, Define what “value of information” means



Community Engagement and Input inot Comparative Effectiveness Research Stakeholder   Laurel K. Leslie, MD, MPH Review where we have been in the course and where we are going, Define communities and community engagement within the context of CER, Delineate key points where community engagement may enhance CER, Identify examples of research strategies and methodologies employed to engage communities



Clinical Practice Guidelines General Evidence Katrin Uhlig, MD, MS Growth of Clinical Practice Guidlines, Process of CPG development, and Challenges in evidence synthesis and guideline development



Predictive Instruments as Decision Support for Diagnostic and Theraputic Decisions: Development and Testing in Clinical Effectiveness Trials General Experimental Harry P. Selker, MD, MSPH Explain the use of predictive instruments are incorporated into the use of medications and other treatments, Discuss the use of comparative effectiveness trials for comparing strategies of care, Discuss the possible use of predictive instruments for efficient and ethical conduct of clinical effectiveness trials



Drug Development in the CER Era Decision General Kenneth I. Kaitin, PhD Asses the economic, regulatory, and political pressures affecting pharmaceutical and biopharmaceutical developers today, Discuss current drug development metrics, including the time, cost, and risk of development, Examine how companies, in response to competitive and economic pressures, are adopting new strategies and practices to improve R&D performance



Using Comparative Effectiveness Research to Reach Employers and Employees Decision Evidence Debra J. Lerner, MS, PhD Identify current and projected healthcare and cost issues facing employers and employees, List workplace policies, practices, and programs that are being used to address health and cost trends, Describe the evidence base for workplace health programs, Identify methodological problems and solutions in developing the evidence base and the role of comparative effectiveness studies, Identify issues related to the dissemination and implementation of evidence from comparative effectiveness studies



Economic and Policy Implications of CER Decision Observational Christopher P. Tompkins, PhD Discuss how performance assesment and financial incentive models have been used to impact transformational changes in healthcare policy, Using specific examples, explain how comparative effectiveness research and outcomes measurement impact value-priced purchasing and the cost of healthcare delivery, Describe how a multidimensional framework for measuring outcomes of care and efficiency assist policymakers to make informed decisions that improve healthcare, Discuss opportunities and roles for use of insurance data to improve healthcare, Identify the differences between chart based clinical process-of-care measures vs clincal outcomes measurement and comparative effectiveness research in healthcare delivery systems



Future Directions in CER General   Thomas W. Concannon, PhD WHY CER, Describe existing CER programs, Describe the IOM priority-setting process and identify key features of the current list of 100 priorities, Describe the role of PCORI in setting the future course for a national CER agenda