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.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Research Scientist Development Award - Research & Training (K01)
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HSR Health Care Research Training SS (HCRT)
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Anderson, Kay
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Brigham and Women's Hospital
United States
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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; 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
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
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
Gagne, J J; Glynn, R J; Rassen, J A et al. (2012) Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring system. Clin Pharmacol Ther 92:80-6
Rassen, Jeremy A; Schneeweiss, Sebastian (2012) Newly marketed medications present unique challenges for nonrandomized comparative effectiveness analyses. J Comp Eff Res 1:109-11

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