Using Electronic Medical Record To Identify Changes In Inpatient Learner Experience

Abstract

Background: COVID-19 has been disruptive to inpatient medical care. While changes in prevalence of inpatient diagnoses have been published, little has been published about the impact on learner exposure to various diagnoses. Such changes are likely impacted by national and global trends, as well as local disease prevalence and policies. We hypothesized that the electronic medical record (EMR) may offer a tool to track learner experiences as they evolve in a time of rapid change. Methods: The top 20 most common diagnoses between April-July 2019 vs April-July 2020 on the resident inpatient internal medicine service were extracted from the Epic EMR and compared. This data was analyzed using a chi squared test and Bonferroni correction to identify statistically significant changes in case distribution in this time frame. Changes over this period were also compared for the nonteaching service. Results: The resident teaching service saw a statistically significant decrease in pulmonary cases (13% vs 2%, p < 0.005) from 2019 to 2020. Acute exacerbation of chronic obstructive pulmonary disease (COPD) and pneumonia, previously the 5th and 7th most common diagnoses in the 2019 period, dropped off the top twenty list for the teaching service. These 2 diagnoses remained on the non-teaching common encounter list, suggesting that COVID-19-related service/team assignments rather than disease prevalence may be a factor. There was also a statistically significant increase from 2019 to 2020 in cases pertaining to substance use intoxication on both teaching and non-teaching teams (0 vs 0.05 and 0 vs 0.02, respectively), mirroring trends in national data. Conclusion: Use of the EMR was able to rapidly identify changes in the most common diagnoses on the teaching service. This may be a tool to monitor the inpatient experience of learners over time, particularly in times of rapid local, regional, or global change.