Addressing Bias from Missing Data in EHR Based Studies of CVD

项目摘要 此NHLBI K01应用程序支持助理教授Nrupen A.Bhavsar博士的职业发展 杜克大学医学院的医学博士。Bhavsar博士是一位慢性病流行病学家 在心血管疾病、慢性肾脏疾病和癌症的流行病学方面进行多学科研究。他很有激情 关于在流行病学、信息学和生物统计学的交叉点从事临床研究的职业。在 获奖期结束后，Bhavsar博士将成为一名独立调查员，应用通过K01获得的知识 开发基于EHR的大规模人群研究，以确定心血管疾病的高危个体 (CVD)事件。通过在数据链接、机器学习和因果推理方面的培训，他将应用缺失的数据 方法进行严格的非随机研究，以改善健康状况。拟议培训的主题领域 并研究了糖尿病和心血管事件在数据关联、机器学习和因果关系中的应用 推论。职业发展目标：获得信息学、生物统计学和 人口科学，以调查使用多卫生系统EHR数据的内在方法学挑战 临床研究。培训方法将利用授课和体验式培训，并辅之以分析 数据来源于多个健康系统、多个州的协作研究。研究人群：接受治疗的患者 北卡罗来纳州或南卡罗来纳州“卡罗莱纳州合作”机构之一的护理(杜克大学医学院 中心、北卡罗来纳大学-CH卫生系统、维克森林浸信会卫生中心，以及9个其他卫生系统合作 在南卡罗来纳州机构的健康科学中)。具体目标：该提案将确定 当患者跨多个医疗系统寻求护理，但EHR数据仅从以下位置获得时，应考虑缺失数据 单一的医疗系统。估计单一机构研究中缺失数据所带来的系统性偏差 确定缺失数据偏差的解释方法可能会提高EHR数据用于临床的能力 研究。预期结果：通过此次NHLBI K01研究科学家职业发展奖，Bhavsar博士 将获得必要的培训和研究经验，以发展大规模的心血管疾病基于电子健康记录的人口研究。

Project Summary 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.