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.
|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|
|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|
|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|
|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|
|Brunelli, Steven M; Rassen, Jeremy A (2013) Emerging analytical techniques for comparative effectiveness research. Am J Kidney Dis 61:13-7|
|Gagne, Joshua J; Rassen, Jeremy A; Walker, Alexander M et al. (2012) Active safety monitoring of new medical products using electronic healthcare data: selecting alerting rules. Epidemiology 23:238-46|
|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|
|Schneeweiss, S; Gagne, J J; Glynn, R J et al. (2011) Assessing the comparative effectiveness of newly marketed medications: methodological challenges and implications for drug development. Clin Pharmacol Ther 90:777-90|
|Rassen, Jeremy A; Glynn, Robert J; Brookhart, M Alan et al. (2011) Covariate selection in high-dimensional propensity score analyses of treatment effects in small samples. Am J Epidemiol 173:1404-13|
|Brookhart, M Alan; Rassen, Jeremy A; Schneeweiss, Sebastian (2010) Instrumental variable methods in comparative safety and effectiveness research. Pharmacoepidemiol Drug Saf 19:537-54|
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