Five analytic challenges in working with electronic health records data to support clinical trials with some solutions.
Electronic health records data are becoming a key data resource in clinical research. Owing to issues of data efficiency, electronic health records data are being used for clinical trials. This includes both large-scale pragmatic trails and smaller-more focused-point-of-care trials. While electronic health records data open up a number of scientific opportunities, they also present a number of analytic challenges. This article discusses five particular challenges related to organizing electronic health records data for analytic purposes. These are as follows: (1) data are not organized for research purposes, (2) data are both densely and irregularly observed, (3) we don't have all data elements we may want or need, (4) data are both cross-sectional and longitudinal, and (5) data may be informatively observed. While laying out these challenges, the article notes how many of these challenges can be addressed by careful and thoughtful study design as well as by integration of clinicians and informaticians into the analytic team.
['Goldstein|Benjamin A|BA|0000-0001-5261-3632']
D002986:Clinical Trials as Topic D003430:Cross-Sectional Studies D003625:Data Collection D057286:Electronic Health Records D006801:Humans D008137:Longitudinal Studies D018579:Patient Selection D064792:Pragmatic Clinical Trials as Topic D012107:Research Design
Electronic health records study design selection bias