TITLE: Statistical Topics in Outcomes Research: Patient-Reported Outcomes, Meta-Analysis, and Health Economics
INSTRUCTOR: Joseph C. Cappelleri, Pfizer Inc, and Thomas Mathew, University of Maryland Baltimore County
MODERATOR: Wenjin Wang


Based in part on the recently published co-edited volume Statistical Topics in Health Economics and Outcomes Research (Alemayehu et al.), this four-hour short course recognizes that, with ever-rising healthcare costs, evidence generation through health economics and outcomes research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. This course highlights three major topics related to HEOR, with objectives to learn about 1) patient-reported outcomes, 2) analysis of aggregate data, and 3) methodological issues in health economic analysis. Key themes on patient-reported outcomes are presented regarding their development and validation: content validity, construct validity, and reliability. Regarding analysis of aggregate data, several areas are elucidated: traditional meta-analysis, network meta-analysis, assumptions, and best practices for the conduct and reporting of aggregated data. For methodological issues on health economic analysis, cost-effectiveness criteria are covered: traditional measures of cost-effectiveness, the cost-effectiveness acceptability curve, statistical inference for cost-effectiveness measures, the fiducial approach (or generalized pivotal quantity approach), and a probabilistic measure of cost-effectiveness. Illustrative examples are used throughout the course to complement the concepts. Attendees are expected to have taken at least one graduate level course in statistics.
Learning Objectives
To understand and critique the major methodological issues in outcomes research on the development and validation of patient-reported outcomes, traditional meta-analysis and network meta-analysis, and health economic analysis.
Main Book Reference:
Alemayehu D, Cappelleri JC, Emir B, Zou KH (editors). Statistical Topics in Health Economics and Outcomes Research. Boca Raton, Florida: Chapman & Hall/CRC Press. 2017.
Other References:
Bebu I, Luta G, Mathew T, Kennedy TA, Agan BK. Parametric cost-effectiveness inference with skewed data. Computational Statistics and Data Analysis. 2016; 94:210–220.
Bebu I, Mathew T, Lachin JM. Probabilistic measures of cost-effectiveness. Statistics in Medicine. 2016; 35:3976-3986.
Cappelleri JC, Zou KH, Bushmakin AG, Alvir JMJ, Alemayehu D, Symonds T. Patient-Reported Outcomes: Measurement, Implementation and Interpretation. Boca Raton, Florida: Chapman & Hall/CRC Press. 2013.

Instructors’ Biography:

Joseph C. Cappelleri, PhD, MPH, MS is an executive director in the Statistical Research and Data Science Center at Pfizer Inc. He earned his M.S. in statistics from the City University of New York (Baruch College), Ph.D. in psychometrics from Cornell University, and M.P.H. in epidemiology from Harvard University. As an adjunct professor, Dr. Cappelleri has served on the faculties of Brown University, University of Connecticut, and Tufts Medical Center. He has delivered numerous conference presentations and has published extensively on clinical and methodological topics, including on regression-discontinuity designs, meta-analyses, and health measurement scales. He is lead author of the book Patient-Reported Outcomes: Measurement, Implementation and Interpretation and has co-authored or co-edited three other books (Phase II Clinical Development of New Drugs, Statistical Topics in Health Economics and Outcomes Research, Design and Analysis of Subgroups with Biopharmaceutical Applications). Dr. Cappelleri is a fellow of the American Statistical Association and president of the New England Statistical Society.

Thomas Mathew, PhD, is Professor, Department of Mathematics & Statistics, University of Maryland Baltimore County (UMBC). He earned his PhD in statistics from the Indian Statistical Institute in 1983, and has been a faculty member at UMBC since 1985. He has delivered numerous conference presentations, nationally and internationally, and has published extensively on methodological and applied topics, including cost-effectiveness analysis, bioequivalence testing, exposure data analysis, meta-analysis, mixed and random effects models, and tolerance intervals. He is the co-author of two books Statistical Tests in Mixed Linear Models and Statistical Tolerance Regions: Theory, Applications and Computation, both published by Wiley. He has served on the Editorial Boards of several journals, and is currently an Associate Editor of the Journal of the American Statistical Association, Journal of Multivariate Analysis, and Sankhya. Dr. Mathew is a Fellow of the American Statistical Association, and a Fellow of the Institute of Mathematical Statistics. He has also been appointed as Presidential Research Professor at his campus.

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