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Published on: February 13, 2020
Development and validation of Trainee Attributable & Automatable Care Evaluations in Real-Time (TRACERs)
Jesse Burk-Rafel1,2, Stefanie S Sebok-Syer3, Ian Larson1
1Division of Hospital Medicine, NYU Langone Health, New York, NY, United States.
Summary
Trainee Attributable & Automatable Care Evaluations in Real-Time (TRACERs) identified significant variation in inpatient diabetes insulin prescribing among residents and institutions. This highlights opportunities for real-time feedback to improve guideline adherence.
Area of Science:
- Medical Education
- Health Informatics
- Endocrinology
Background:
- Inpatient diabetes management presents challenges for resident education.
- Current assessment methods may not capture real-time prescribing behaviors effectively.
Purpose of the Study:
- To develop and validate Trainee Attributable & Automatable Care Evaluations in Real-Time (TRACERs) for inpatient diabetes management.
- To assess the validity of TRACERs for formative feedback.
- To explore variations in resident and institutional performance.
Main Methods:
- Two TRACERs were developed based on type 2 diabetes guidelines.
- Electronic health record (EHR) data were extracted for 35 variables.
- Criterion validity was established through expert review.
- A retrospective cohort analysis was conducted.
Main Results:
- Automated EHR data extraction achieved high sensitivity (≥96%) and specificity (≥95%).
- Significant variation in TRACER #1 and TRACER #2 occurrence was observed across three residency programs (P < .001).
- Four distinct resident insulin-ordering profiles were identified, with resident-level variation exceeding program-level differences.
Conclusions:
- TRACERs demonstrate substantial institutional and resident variation in insulin prescribing, revealing guideline deviations.
- The system shows potential for real-time formative feedback in diabetes care.
- Multi-institutional implementation identified scalability barriers, necessitating further refinement and validation.
