CIRS/SWB WEBINAR ON STATISTICAL DATA INTEGRATION IN HEALTH POLICY BY SUSAN PADDOCK

CIRS/SWB WEBINAR ON STATISTICAL DATA INTEGRATION IN HEALTH POLICY BY SUSAN PADDOCK

Dear Colleagues,

We are excited to announce our upcoming CIRS/SWB Webinar titled “An Overview of Statistical Data Integration in Health Policy” by Dr.  Susan Paddock to take place on July 24, 12-1:30 PM ET.

 Our webinar series, sponsored jointly by the American Statistical Association’s Committee on International Relations in Statistics (CIRS) and by Statistics Without Borders (SWB), provides introductory lectures by experts on important topics of current interest, and is aimed at an international audience.

 Please join us by registering for this webinar 

https://amstat.zoom.us/webinar/register/WN_rj7lK06AQcSJpHok8MbLTA#/registration

and help us spread the word by forwarding this to colleagues you think might be interested.  Participation is free but registration is required.   We have attached a flyer for the event and provide more information below.   We look forward to seeing you there!

Tile: “An Overview of Statistical Data Integration in Health Policy”

 Speaker: Dr. Susan Paddock, NORC at the University of Chicago

Abstract: Data integration techniques leverage the relative strengths of input sources to obtain a blended source that is richer and more informative than any single component. This is important for health policy, as analyses typically rely on a variety of data sources, most of which were not designed for the intended research use case. These data sources include electronic health records, health care claims and other administrative data, surveys, and more. In this webinar, an overview of opportunities and challenges of statistical data integration to facilitate health policy analysis will be provided. The presentation will include the use of a data quality framework for structuring data quality assessments of candidate input data sources. The statistical techniques to be presented include combining probability surveys with nonprobability (convenience) sources, blending randomized controlled trial data with data representing ‘real world populations,’ small area estimation, and method for expanding the number of variables in a dataset via record linkage or statistical matching (data fusion). Motivating examples will be provided to illustrate concepts.

 About the presenter: Dr. Susan Paddock is Chief Scientist and Executive Vice President at NORC at the University of Chicago. Her team at NORC includes statisticians, survey methodologists, data scientists, quantitative social scientists, and AI researchers who are engaged in projects for federal, other governmental, and private sector clients on topics that span multiple substantive research areas including education, health, global, and public affairs. Susan has published methodological developments in the areas of Bayesian methods, causal inference, hierarchical modeling, longitudinal data analysis, and missing data techniques. Susan is a fellow of the American Statistical Association and has served on editorial boards for several journals, including Annals of Applied Statistics, Journal of the American Statistical Association, and Harvard Data Science Review.

Carolina Franco,

Past Chair, Committee on International Relations in Statistics

Carolina Franco

Principal Statistician

Statistics and Data Science

(240) 278-0746

franco-carolina@norc.org

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