November 6: Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources - In Person at ISPOR Europe 2022
Retrospective studies require strong principles of epidemiologic study design and complex analytical methods to adjust for bias and confounding. This course will provide an overview of the structures of commonly encountered retrospective data sources with a focus on large administrative data, as well as highlight design and measurement issues investigators face when developing a protocol using retrospective observational data. Approaches to measure and control for patient mix, including patient comorbidity and the use of restriction and stratification, will be presented. Linear multivariable regression, logistic regression, and propensity scoring analytic techniques will be presented and include examples using SAS code that can later be used by participants. This course is an introductory course designed to prepare participants to take intermediate and advanced observational research courses.
Associate Professor of Health Economics
Section for Neurogeriatrics, Department of Neurobiology
Care Sciences and Society
Karolinska Institutet
Stockholm, Sweden
Bradley C. Martin, PharmD, RPh, PhD
Professor
Division of Pharmaceutical Evaluation and Policy
University of Arkansas for Medical Sciences College of Pharmacy
Little Rock, AR, USA
November 6, 2022
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Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources
LEVEL: Introductory
TRACK: Study Approaches
LENGTH: 4 Hours | Course runs 1 day
This short course will be offered in-person at the ISPOR Europe 2022 conference. Separate registration is required. Visit the ISPOR Europe 2022 website to register and learn more.
DESCRIPTION
Retrospective studies require strong principles of epidemiologic study design and complex analytical methods to adjust for bias and confounding. This course will provide an overview of the structures of commonly encountered retrospective data sources with a focus on large administrative data, as well as highlight design and measurement issues investigators face when developing a protocol using retrospective observational data. Approaches to measure and control for patient mix, including patient comorbidity and the use of restriction and stratification, will be presented. Linear multivariable regression, logistic regression, and propensity scoring analytic techniques will be presented and include examples using SAS code that can later be used by participants. This course is an introductory course designed to prepare participants to take intermediate and advanced observational research courses.FACULTY MEMBERS
Linus Jönsson, PhD, MD, MScAssociate Professor of Health Economics
Section for Neurogeriatrics, Department of Neurobiology
Care Sciences and Society
Karolinska Institutet
Stockholm, Sweden
Bradley C. Martin, PharmD, RPh, PhD
Professor
Division of Pharmaceutical Evaluation and Policy
University of Arkansas for Medical Sciences College of Pharmacy
Little Rock, AR, USA
Basic Schedule:
4 Hours | Course runs 1 Day