Course Description
Embark on a comprehensive journey into the world of Comparative Effectiveness Research (CER) and Patient-Centered Outcomes Research (PCOR) with this introductory course from MDAndersonX. This course, supported by the Agency for Healthcare Research and Quality, offers a deep dive into the critical skills needed for evidence-based healthcare decision-making. You'll master the art of conducting systematic reviews, performing meta-analyses, and interpreting complex scientific literature. By the end of this course, you'll be equipped with the tools to navigate the vast sea of biomedical information and transform it into actionable insights for improved patient care.
Prerequisites
While the introductory course (CERTaIN.1x) is recommended, it is not mandatory. This course is designed for individuals with a basic understanding of healthcare research and statistics. Familiarity with medical terminology and basic research concepts would be beneficial.
Who This Course Is For
This course is ideal for healthcare professionals, researchers, policymakers, and students interested in evidence-based medicine, healthcare quality improvement, and patient-centered outcomes research. It's particularly valuable for those looking to enhance their skills in comparative effectiveness research and make data-driven decisions in healthcare.
Syllabus
1. Overview of Systematic Reviews
Knowledge synthesis and the knowledge-to-action process, benefits and limitations of systematic reviews, steps of a systematic review and levels of evidence
2. Finding and Managing the Evidence from the Biomedical Literature
Searching published and unpublished materials systematically
3. Intervention Reviews Methodology
Selecting and appraising studies, strategies for collecting and analyzing data, reporting and updating systematic reviews
4. Meta-Analysis of Clinical Trials: Direct Comparisons
Qualitative and quantitative synthesis, data analysis models, heterogeneity, reporting methods for meta-analyses
5. Introduction to Meta-Analysis: Indirect Comparisons
Indirect comparisons, evidence networks, effect modifiers and bias sources
6. Meta-Analysis of Non-Randomized Studies
Risks of bias in non-randomized studies, meta-regression techniques, reporting meta-analyses of non-randomized studies
7. Diagnostic Test Evaluation
Purposes for medical testing, precision and accuracy, measures of validity for diagnostic/screening tests, likelihood ratio and ROC curves for test performance analysis
8. Meta-Synthesis
Methods for collecting and synthesizing data, reporting meta-synthesis findings
9. Clinical Practice Guidelines
Guideline development process, evidence evaluation, guideline evaluation and revision
10. Economic Evaluation
Clinical decision analysis and economic evaluation, costs and methods for economic evaluation, cost-effectiveness and cost analysis, steps for economic evaluation
11. Decision Analysis for Outcomes Research
Decision analysis and modeling, Markov modeling, capturing uncertainty in models, examples of decision modeling in cancer outcomes research