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Using Electronic Medical Record To Identify Changes In Inpatient Learner Experience.

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Area of Science:

  • Medical Education
  • Inpatient Care
  • Epidemiology

Background:

  • COVID-19 significantly disrupted standard inpatient medical care delivery.
  • While changes in diagnosis prevalence are documented, the impact on medical learner exposure remains understudied.
  • Electronic Medical Records (EMR) offer a potential tool to monitor these evolving learner experiences.

Purpose of the Study:

  • To investigate the impact of COVID-19 on the distribution of inpatient diagnoses encountered by internal medicine residents.
  • To assess the utility of the Electronic Medical Record (EMR) in tracking changes in learner clinical exposure.

Main Methods:

  • A retrospective analysis compared the top 20 most common diagnoses on the resident internal medicine service between April-July 2019 and April-July 2020.
  • Data was extracted from the Epic EMR and analyzed using chi-squared tests with Bonferroni correction.
  • Comparisons were also made with the non-teaching service to differentiate between disease prevalence and service assignment effects.

Main Results:

  • The resident teaching service experienced a significant decrease in pulmonary cases (13% to 2%), with COPD exacerbations and pneumonia dropping out of the top 20 diagnoses.
  • Pulmonary cases remained prevalent on the non-teaching service, suggesting service assignment, not just prevalence, influenced resident exposure.
  • Both teaching and non-teaching services saw a significant increase in substance use intoxication cases, aligning with national trends.

Conclusions:

  • EMR data can rapidly identify shifts in common diagnoses encountered by medical residents.
  • This approach provides a valuable method for monitoring the inpatient clinical learning environment during periods of significant change.
  • The findings highlight the need to consider service-specific assignments when evaluating learner exposure to diagnoses during public health emergencies.