The role and limitations of electronic medical records versus patient interviews for determining symptoms of, underlying comorbidities of, and medication use by patients with COVID-19

• DOI: 10.1093/aje/kwae079
• Publication Date: 2024-05-22T11:22:28Z
• Authors: Raymond A Soto; Grace M Vahey; Kristen E Marshall; Emily McDonald; Rachel Herlihy; Helen M Chun; Marie E Killerby; Breanna Kawasaki; Claire M Midgley; Nisha B Alden; Jacqueline E Tate; J Erin Staples; Colorado Investig...
• Keywords: Male; Adult; SARS-CoV-2; COVID-19; Comorbidity; Middle Aged; Data Accuracy; Interviews as Topic; 0302 clinical medicine; 0202 electrical engineering, electronic engineering, information engineering; Humans; Electronic Health Records; Female; Aged

Abstract Electronic medical records (EMRs) are important for rapidly compiling information to determine disease characteristics (eg, symptoms) and risk factors (eg, underlying comorbidities, medications) for disease-related outcomes. To assess EMR data accuracy, agreement between EMR abstractions and patient interviews was evaluated. Symptoms, medical history, and medication use among patients with COVID-19 collected from EMRs and patient interviews were compared using overall agreement (ie, same answer in EMR and interview), reported agreement (yes answer in both EMR and interview among those who reported yes in either), and κ statistics. Overall, patients reported more symptoms in interviews than in EMR abstractions. Overall agreement was high (≥50% for 20 of 23 symptoms), but only subjective fever and dyspnea had reported agreement of ≥50%. The κ statistics for symptoms were generally low. Reported medical conditions had greater agreement with all condition categories (n = 10 of 10) having ≥50% overall agreement and half (n = 5 of 10) having ≥50% reported agreement. More nonprescription medications were reported in interviews than in EMR abstractions, leading to low reported agreement (28%). Discordance was observed for symptoms, medical history, and medication use between EMR abstractions and patient interviews. Investigations using EMRs to describe clinical characteristics and identify risk factors should consider the potential for incomplete data, particularly for symptoms and medications.