With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility. This work explores challenges in how different experimental design decisions can influence results using a specific example of breast cancer patients undergoing excision and reconstruction surgeries from EMRs in an academic hospital and the Veterans Health Administration (VHA) We discuss emerging strategies that will mitigate these limitations, including data sharing, application of natural language processing, and improved EMR user design.
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