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Addressing Bias from Missing Data in EHR Based Studies of CVD

解决基于 EHR 的 CVD 研究中缺失数据带来的偏差

基本信息

批准号：
10458507
负责人：
Nrupen Bhavsar
金额：
$ 16.58万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2023-09-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10458507
关键词：
Academic Medical Centers Accounting Address Area Award Baptist Church Biometry Cardiovascular Diseases Caring Chronic Disease Chronic Kidney Failure Clinical Clinical Data Clinical Informatics Clinical Research Cohort Studies Competence Complement Data Data Analyses Data Element Data Linkages Data Pooling Data Science Data Store Development Development Plans Diabetes Mellitus Doctor of Philosophy Electronic Health Record Epidemiologic Methods Epidemiologist Epidemiology Event Goals Health Health Sciences Health system Healthcare Hospitalization Individual Informatics Institution K-Series Research Career Programs Knowledge Lead Legal Machine Learning Medicine Meta-Analysis Methodology Methods Myocardial Infarction National Heart, Lung, and Blood Institute North Carolina Outcome Outcomes Research Patient Care Patients Pharmaceutical Preparations Population Population Sciences Population Study Privacy Publishing Renal carcinoma Reporting Research Research Methodology Research Personnel Research Priority Risk Risk Factors Scientist South Carolina Stroke Training Universities Work base cardiovascular disorder epidemiology cardiovascular disorder risk cardiovascular health care seeking career career development clinical care cohort comorbidity data quality distributed data electronic data epidemiologic data epidemiology study experience forest high risk improved machine learning method medical schools multidisciplinary novel patient population population health practical application professor randomized trial skills study population

项目摘要

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.

项目摘要这个NHLBI K 01应用程序支持Nrupen A博士的职业发展。Bhavsar，博士，助理教授他是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了多学科研究。他热衷关于在流行病学、信息学和生物统计学的交叉点从事临床研究的职业。在奖励期结束后，Bhavsar博士将成为一名独立研究者，应用通过本K 01获得的知识开展大规模基于EHR的人群研究，以确定心血管疾病高危人群 (CVD)事件通过数据链接、机器学习和因果推理方面的训练，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。拟议培训的专题领域和研究是糖尿病和事件CVD事件在数据链接，机器学习和因果关系的应用，推论职业发展目标：在信息学，生物统计学和生物统计学领域获得跨学科能力。人口科学，以调查使用多卫生系统EHR数据的固有方法挑战，临床研究培训方法将利用教学和体验式培训，并辅之以数据来源于多个卫生系统、多个州的研究协作。研究人群：接受在北卡罗来纳州或南卡罗来纳州的一个“卡罗莱纳协作”机构（杜克大学医学院）接受护理中心、UNC-CH卫生系统、维克森林浸信会卫生中心和9个其他卫生系统合作在南卡罗来纳州的健康科学机构内）。具体目标：本提案将确定各种办法，当患者在多个卫生系统中寻求护理时，可以解释缺失的数据，但EHR数据仅可从单一的卫生系统。估计单机构研究缺失数据引入的系统偏倚，确定用于解释缺失数据偏差的方法可以提高EHR数据用于临床的能力， research.预期结果：通过NHLBI K 01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，以开发大规模的基于EHR的CVD人群研究。

项目成果

期刊论文数量（12）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Prevalence and predictors of no-shows to physical therapy for musculoskeletal conditions.

DOI：
10.1371/journal.pone.0251336
发表时间：
2021
期刊：
PloS one
影响因子：
3.7
作者：
Bhavsar NA;Doerfler SM;Giczewska A;Alhanti B;Lutz A;Thigpen CA;George SZ
通讯作者：
George SZ

Predicting Recurrent Care Seeking of Physical Therapy for Musculoskeletal Pain Conditions.

预测肌肉骨骼疼痛状况的物理治疗的复发性护理寻求。

DOI：
10.1093/pm/pnab154
发表时间：
2021
期刊：
Pain medicine (Malden, Mass.)
影响因子：
0
作者：
George,StevenZ;Giczewska,Anna;Alhanti,Brooke;Lutz,AdamD;Shanley,Ellen;Thigpen,CharlesA;Bhavsar,NrupenA
通讯作者：
Bhavsar,NrupenA

Response to the Comment from Riddle and Ghomrawi.

对 Riddle 和 Ghomrawi 评论的回应。

DOI：
10.1016/j.jpain.2022.02.001
发表时间：
2022
期刊：
The journal of pain
影响因子：
0
作者：
George,StevenZ;Bolognesi,MichaelP;Bhavsar,NrupenA;Penrose,ColinT;Horn,MaggieE
通讯作者：
Horn,MaggieE

A Prospective Multicenter Evaluation of Initial Treatment Choice in Metastatic Renal Cell Carcinoma Prior to the Immunotherapy Era: The MaRCC Registry Experience.