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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

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US Internal Medicine Residents' Inpatient Learning Experience Variation Revealed Through Electronic Health Record

Sean Tackett^1,2, Bahareh Modanloo², Heather Sateia³

¹Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Teaching and Learning in Medicine

|April 7, 2025

Summary

This summary is machine-generated.

Internal medicine residents manage a wide range of clinical conditions, with significant variation in patient encounters even within the same postgraduate year. Electronic health record data reveals differences between actual experiences and the American Board of Internal Medicine (ABIM) exam blueprint.

Keywords:

Assessment graduate medical education precision medical education

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Area of Science:

Medical Education
Health Informatics
Internal Medicine Residency Training

Background:

Physician residents' clinical experiences are crucial for practice readiness but are not well-characterized.
Electronic health records (EHRs) offer a rich source of data on resident clinical activities.
Existing studies have limited use of EHR data to define resident learning experiences.

Purpose of the Study:

To characterize the clinical conditions managed by internal medicine residents using EHR data.
To compare resident experiences with the American Board of Internal Medicine (ABIM) Certification Exam Blueprint.
To identify variations in clinical encounters among residents at different postgraduate years (PGYs).

Main Methods:

Extracted EHR data from Johns Hopkins Hospital internal medicine residency program (July 2018-June 2019).
Identified clinical conditions using ICD-10-CM discharge codes and categorized them per the ABIM Blueprint.
Analyzed individual resident encounters, comparing condition frequencies across PGYs and against the ABIM Blueprint.

Main Results:

19,129 admissions involving 135 residents were analyzed.
Most common ABIM categories encountered: Cardiovascular (20.4%), Infectious Diseases (19.5%), Gastroenterology (11.2%).
Significant discrepancies noted: excess in Infectious Diseases (10.5%) and Cardiovascular (6.4%), deficits in Rheumatology/Orthopedics (6.1%) and Endocrinology (5.5%).
Substantial variation in patient admissions and clinical condition percentages existed among residents in the same PGY.

Conclusions:

Inpatient clinical experiences vary significantly among residents within the same program.
EHR data analysis can reveal gaps between resident training and examination requirements.
Insights from EHR data can inform precision medical education to enhance learning and patient outcomes.