This NHLBI K01 application supports the career development of Dr. Nrupen A. Bhavsar, PhD, an Assistant Professor of Medicine at the Duke University School of Medicine. Dr. Bhavsar is a chronic disease epidemiologist who has performed multidisciplinary studies in the epidemiology of CVD, chronic kidney disease and cancer. He is passionate about pursuing a career in clinical research at the intersection of epidemiology, informatics, and biostatistics. At the end of the award period, Dr. Bhavsar will be an independent investigator applying knowledge gained through this K01 to develop large scale EHR-based population studies that identify individuals at high risk for cardiovascular disease (CVD) events. Through training in data linkage, machine learning, and causal inference, he will apply missing data methods to conduct rigorous non-randomized studies to improve health. The topical areas of the proposed training and research are diabetes and incident CVD events in the application of data linkage, machine learning, and causal inference. Career development aim: Obtain transdisciplinary competencies within informatics, biostatistics, and population sciences to investigate methodological challenges inherent in the use of multi-health system EHR data for clinical research. The training approach will leverage didactic and experiential training complemented by analyses of data derived from a multi-health system, multi-state research collaborative. Study population: Patients who received care at one of the North Carolina or South Carolina ?Carolinas Collaborative? institutions (Duke University Medical Center, UNC-CH Health System, Wake Forest Baptist Health Center, and 9 additional health systems collaborating within the Health Sciences of South Carolina institutions).
Specific aims : This proposal will identify approaches to account for missing data when patients seek care across multiple health systems but EHR data is only available from a single health system. Estimating the systemic bias introduced by missing data for single institution studies and identifying methods for accounting for missing data biases may improve the ability of EHR data to be used for clinical research. Anticipated results: Through this NHLBI K01 Research Scientist Career Development Award, Dr. Bhavsar will acquire essential training and research experience to develop large scale EHR-based population studies in CVD.
Data from the electronic health records (EHR) are increasingly being used for clinical research, yet there is limited information on the best approaches to address the methodological limitations of the EHR, such as missing data. In patients with diabetes at risk of cardiovascular disease events, I will examine the impact that missing data has on the ability to use the EHR for clinical research and develop approaches to address the biases resulting from missing data.
