USF-LVHN SELECT
Harnessing electronic medical records to advance research on multiple sclerosis.
Publication/Presentation Date
3-1-2019
Abstract
BACKGROUND: Electronic medical records (EMR) data are increasingly used in research, but no studies have yet evaluated similarity between EMR and research-quality data and between characteristics of an EMR multiple sclerosis (MS) population and known natural MS history.
OBJECTIVES: To (1) identify MS patients in an EMR system and extract clinical data, (2) compare EMR-extracted data with gold-standard research data, and (3) compare EMR MS population characteristics to expected MS natural history.
METHODS: Algorithms were implemented to identify MS patients from the University of California San Francisco EMR, de-identify the data and extract clinical variables. EMR-extracted data were compared to research cohort data in a subset of patients.
RESULTS: We identified 4142 MS patients via search of the EMR and extracted their clinical data with good accuracy. EMR and research values showed good concordance for Expanded Disability Status Scale (EDSS), timed-25-foot walk, and subtype. We replicated several expected MS epidemiological features from MS natural history including higher EDSS for progressive versus relapsing-remitting patients and for male versus female patients and increased EDSS with age at examination and disease duration.
CONCLUSION: Large real-world cohorts algorithmically extracted from the EMR can expand opportunities for MS clinical research.
Volume
25
Issue
3
First Page
408
Last Page
418
ISSN
1477-0970
Published In/Presented At
Damotte, V., Lizée, A., Tremblay, M., Agrawal, A., Khankhanian, P., Santaniello, A., Gomez, R., Lincoln, R., Tang, W., Chen, T., Lee, N., Villoslada, P., Hollenbach, J. A., Bevan, C. D., Graves, J., Bove, R., Goodin, D. S., Green, A. J., Baranzini, S. E., Cree, B. A., … Gourraud, P. A. (2019). Harnessing electronic medical records to advance research on multiple sclerosis. Multiple sclerosis (Houndmills, Basingstoke, England), 25(3), 408–418. https://doi.org/10.1177/1352458517747407
Disciplines
Medical Education | Medicine and Health Sciences
PubMedID
29310490
Department(s)
USF-LVHN SELECT Program, USF-LVHN SELECT Program Students
Document Type
Article