Exploring Discrepancies: Analyzing Electronic Medical Records Data Against Direct Observations

An Electronic Medical Record, or EMR, is a digital way to keep track of patient information. EMRs are used by healthcare providers for diagnosis, treatment, and clinic decisions. There are several factors that impact the accuracy of EMRs, including data entry accuracy, backend configuration, and the time of documentation. This project aims to improve the patient and worker experience in primary care clinics, focusing on the influence of EMR. Through observations at the University of Virginia's University Physicians Primary Care Clinic, appointment milestones were recorded to create a dataset for comparison with the EMR dataset. Discrepancies between in-person observations and EMR data were noted. Metrics were applied to analyze decision implications based on each dataset. This paper underscores the importance of accommodating discrepancies for reliable healthcare information and decision-making.