Pan-Canadian Electronic Medical Record Diagnostic and Unstructured Text Data for Capturing PTSD: Retrospective Observational Study

Leanne Kosowan; Alexander Singer; Farhana Zulkernine; Hasan Zafari; Marcello Nesca; Dhasni Muthumuni

doi:10.2196/41312

Pan-Canadian Electronic Medical Record Diagnostic and Unstructured Text Data for Capturing PTSD: Retrospective Observational Study

JMIR Med Inform. 2022 Dec 13;10(12):e41312. doi: 10.2196/41312.

Authors

Leanne Kosowan¹, Alexander Singer¹, Farhana Zulkernine², Hasan Zafari², Marcello Nesca³, Dhasni Muthumuni⁴

Affiliations

¹ Department of Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
² School of Computing, Queen's University, Kingston, ON, Canada.
³ Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada.
⁴ Department of Psychiatry, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.

PMID: 36512389
PMCID: PMC9795397
DOI: 10.2196/41312

Abstract

Background: The availability of electronic medical record (EMR) free-text data for research varies. However, access to short diagnostic text fields is more widely available.

Objective: This study assesses agreement between free-text and short diagnostic text data from primary care EMR for identification of posttraumatic stress disorder (PTSD).

Methods: This retrospective cross-sectional study used EMR data from a pan-Canadian repository representing 1574 primary care providers at 265 clinics using 11 EMR vendors. Medical record review using free text and short diagnostic text fields of the EMR produced reference standards for PTSD. Agreement was assessed with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy.

Results: Our reference set contained 327 patients with free text and short diagnostic text. Among these patients, agreement between free text and short diagnostic text had an accuracy of 93.6% (CI 90.4%-96.0%). In a single Canadian province, case definitions 1 and 4 had a sensitivity of 82.6% (CI 74.4%-89.0%) and specificity of 99.5% (CI 97.4%-100%). However, when the reference set was expanded to a pan-Canada reference (n=12,104 patients), case definition 4 had the strongest agreement (sensitivity: 91.1%, CI 90.1%-91.9%; specificity: 99.1%, CI 98.9%-99.3%).

Conclusions: Inclusion of free-text encounter notes during medical record review did not lead to improved capture of PTSD cases, nor did it lead to significant changes in case definition agreement. Within this pan-Canadian database, jurisdictional differences in diagnostic codes and EMR structure suggested the need to supplement diagnostic codes with natural language processing to capture PTSD. When unavailable, short diagnostic text can supplement free-text data for reference set creation and case validation. Application of the PTSD case definition can inform PTSD prevalence and characteristics.

Keywords: EHR; NLP; PTSD; electronic health records; medical informatics; natural language processing; posttraumatic stress disorder; primary health care; stress disorders, posttraumatic.

©Leanne Kosowan, Alexander Singer, Farhana Zulkernine, Hasan Zafari, Marcello Nesca, Dhasni Muthumuni. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 13.12.2022.