The rising cost of healthcare and the rising prevalence of cardiovascular disease (CVD) and its associated interventions have fostered the demand for sound comparative effectiveness (CE) data. However, specific methods and data are required for treatments and interventions delivered in-hospital. The candidate brings training in advanced epidemiology methods as well as ten years of computer industry experience and aspires to develop novel data sources and methods for CE research. These methods are intended to provide an extended toolbox for CE researchers and, for three clinical examples related to CVD, specific knowledge to practicing clinicians. Drs. Sebastian Schneeweiss, Jerry Avorn, and Robert Glynn will serve as mentors. Collaborators will include Drs. Kenneth Rothman and David Bates. The applicant will enroll in coursework and seminars to gain specific medical and hospital management knowledge, and will attend national conferences to share and gain learnings about epidemiologic techniques. The applicant will have the resources of the Brigham &Women's Hospital's Division of Pharmacoepidemiology and Pharmacoeconomics available.
The aims of this project are to (1) assess hospital variability in use of treatments, specifically as it informs instrumental variable (IV) analysis for CE;(2) develop a linked in- and out-of-hospital database and to evaluate that database's ability to provide confounding adjustment;(3) develop and extend instrumental variable and propensity score techniques;and (4) develop techniques to provide automated confounding adjustment from electronic medical record (EMR) data. Three CVD-related exposures will be considered, two drugs (bivalirudin and nesirtide) and a device (drug-eluting stents). Each will be compared to established treatments. This award would play an important role in this applicant's development as an outstanding investigator who can provide leadership in CE methodology and research.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01HS018088-03
Application #
8072070
Study Section
HSR Health Care Research Training SS (HCRT)
Program Officer
Anderson, Kay
Project Start
2009-07-01
Project End
2014-06-30
Budget Start
2011-07-01
Budget End
2012-06-30
Support Year
3
Fiscal Year
2011
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Gagne, Joshua J; Wang, Shirley V; Rassen, Jeremy A et al. (2014) A modular, prospective, semi-automated drug safety monitoring system for use in a distributed data environment. Pharmacoepidemiol Drug Saf 23:619-27
Toh, Sengwee; Gagne, Joshua J; Rassen, Jeremy A et al. (2013) Confounding adjustment in comparative effectiveness research conducted within distributed research networks. Med Care 51:S4-10
Rassen, Jeremy A; Shelat, Abhi A; Franklin, Jessica M et al. (2013) Matching by propensity score in cohort studies with three treatment groups. Epidemiology 24:401-9
Brunelli, Steven M; Rassen, Jeremy A (2013) Emerging analytical techniques for comparative effectiveness research. Am J Kidney Dis 61:13-7
Bateman, Brian T; Bykov, Katsiaryna; Choudhry, Niteesh K et al. (2013) Type of stress ulcer prophylaxis and risk of nosocomial pneumonia in cardiac surgical patients: cohort study. BMJ 347:f5416
Rassen, Jeremy A; Shelat, Abhi A; Myers, Jessica et al. (2012) One-to-many propensity score matching in cohort studies. Pharmacoepidemiol Drug Saf 21 Suppl 2:69-80
Rassen, Jeremy A; Schneeweiss, Sebastian (2012) Using high-dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system. Pharmacoepidemiol Drug Saf 21 Suppl 1:41-9
Rassen, Jeremy A; Glynn, Robert J; Rothman, Kenneth J et al. (2012) Applying propensity scores estimated in a full cohort to adjust for confounding in subgroup analyses. Pharmacoepidemiol Drug Saf 21:697-709
Schneeweiss, Sebastian; Rassen, Jeremy A; Glynn, Robert J et al. (2012) Supplementing claims data with outpatient laboratory test results to improve confounding adjustment in effectiveness studies of lipid-lowering treatments. BMC Med Res Methodol 12:180
Polinski, Jennifer M; Schneeweiss, Sebastian; Glynn, Robert J et al. (2012) Confronting ""confounding by health system use"" in Medicare Part D: comparative effectiveness of propensity score approaches to confounding adjustment. Pharmacoepidemiol Drug Saf 21 Suppl 2:90-8

Showing the most recent 10 out of 17 publications