While randomized controlled trials are considered to be the «gold standard» in health research, they cannot always be performed, for ethical or practical reasons. Observational studies gather information from data that has already been collected, or by observing and measuring patients’ changes in health status and their response to interventions outside of a clinical trial. In this course, you will learn to identify the characteristics of observational studies, to interpret the results of observational studies, and to describe the use of health registries in comparative effectiveness research (CER).
This course includes the following 11 lectures:
Overview of Using Observational Data in Comparative Effectiveness Research (CER)
Cancer Registries and Data Linkage
SEER-Medicare and Other Data Sources
Overview of Analytic Methods I
Overview of Analytic Methods II
Longitudinal Data Analysis
Advanced Methods in CER I
Advanced Methods in CER II
Survival Analysis
Analysis of Medical Cost Data in Observational Studies
Healthcare Policy Research
This course is intended for anyone interested in comparative effectiveness research (CER) and patient-centered outcomes research (PCOR) methods.
This course is supported by grant number R25HS023214 from the Agency for Healthcare Research and Quality.
Syllabus
Overview of Using Observational Data in Comparative Effectiveness Research (CER)
When to use observational studies in CER
Observational study biases
Observational study data sources
Cancer Registries and Data Linkage
Data linkage definition
Why cancer registries link their data
Basics of data linkage methods
SEER-Medicare and Other Data Sources
Uses of cancer registry data
Overview of Analytic Methods I
Correlation definition
Statistical methods for continuous outcome variables
Simple linear regression and multiple linear regression
Overview of Analytic Methods II
Statistical methods for categorical data
Mantel Haenszel Method
Logistic regression
Longitudinal Data Analysis
Longitudinal data situations and the problems of repeated measures
Common approaches to measure change over time
Understanding basic results obtained from longitudinal analysis of linear and logistic regression
Advanced Methods in CER I
Limitations of randomized clinical trials and advantages of observational studies
Propensity score definition and estimation
Checking the proper use of propensity scores
Advanced Methods in CER II
Endogeneity bias definition
Conditions and properties of instrumental variable estimation and models
Survival Analysis
Censoring and person-time
Application of life tables
Kaplan Meier estimator
Using the log-rank test to compare survival curves
Hazard function definition and hazard ratio computation
Applying the Cox proportional hazards model
Analysis of Medical Cost Data in Observational Studies
Importance of medical cost analysis
Basic elements of medical cost data
Types of medical cost studies and their analytical methods
Healthcare Policy Research
Objectives and stages of the policy-making process
Comparison and contrast of CER and policy research
Policy changes and evaluation results of a case study