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Characterization and validation of electronic medical record data for pharmacoepidemiologic research
Tyler Schneider1,2, Tanvi Punjani1, Jessyca Matos Silva1
1Clinical Pharmacology Research, Research Institute of St Joe's Hamilton, Hamilton, ON, Canada.
Frontiers in Pharmacology
|August 5, 2026
Summary
Electronic medical record (EMR) data quality in Canadian hospitals was assessed using Epic EMR. While demographics and medication data showed high validity, diagnoses like major adverse cardiac events (MACE) required linkage with external databases for accuracy.
Area of Science:
- Health Informatics
- Pharmacoepidemiology
- Data Quality Assessment
Background:
- Electronic medical records (EMRs) are crucial for pharmacoepidemiologic research.
- Limited data exists on the quality of Canadian hospital EMR data.
Purpose of the Study:
- To assess the validity of data within the Epic EMR system.
- To evaluate data quality for key pharmacoepidemiologic research themes, specifically QT-prolonging medications and major adverse cardiac events (MACE).
Main Methods:
- Developed an entity relationship diagram (ERD) to navigate over 20,000 tables.
- Employed computational validation (comparing with Epic SlicerDicer and CIHI-DAD) and manual validation (chart review).
- Utilized percent agreement with 95% confidence intervals to quantify data validity.
Main Results:
- The ERD identified 43 essential tables for pharmacoepidemiologic research.
- Demographics, medication exposures, and most timestamps demonstrated >95% agreement.
- MACE (excluding death) and certain comorbidities showed <90% agreement, necessitating linkage with the Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD).
Conclusions:
- Not all data fields in the Epic EMR are sufficiently valid for pharmacoepidemiologic research without external data linkage.
- Linked, human-coded data is essential for improving the accuracy of certain diagnoses within EMRs.
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