Identifying problematic opioid use in electronic health record data: Are we looking in the right place?

Lori Schirle, PhD; Shinwho Kwun; Ashley Suh; Sandra Sanchez-Roige, PhD; Alvin D. Jeffery, PhD; David C. Samuels, PhD

doi:10.5055/jom.2023.0754

Authors

Lori Schirle, PhD https://orcid.org/0000-0003-2551-019X
Shinwho Kwun
Ashley Suh
Sandra Sanchez-Roige, PhD
Alvin D. Jeffery, PhD
David C. Samuels, PhD

DOI:

https://doi.org/10.5055/jom.2023.0754

Keywords:

opioid use disorder, electronic health records, patient communications, opioid prescriptions, chronic pain

Abstract

Objective: To examine the value of data obtained outside of regular healthcare visits (clinical communications) to detect problematic opioid use in electronic health records (EHRs).

Design: A retrospective cohort study.

Participants: Chronic pain patient records in a large academic medical center.

Interventions: We compared evidence for problematic opioid use in (1) clinic notes, (2) clinical communications, and (3) full EHR data. We analyzed keyword counts and calculated concordance and Cohen’s κ between data sources.

Main outcome measure: Evidence of problematic opioid use in EHR defined as none, some, or high.

Results: Twenty-six percent of records were discordant in determination of problematic opioid use between clinical communications and clinic notes. Of these, 54 percent detected more evidence in clinical communications, and 46 percent in clinic notes. Compared to full EHR review, clinic notes exhibited higher concordance (78 percent; κ = 0.619) than clinical communications (60 percent; κ = 0.290).

Conclusion: Clinical communications are a valuable addition to opioid HER research.

Author Biographies

Lori Schirle, PhD

Assistant Professor, Vanderbilt University School of Nursing, Nashville, Tennessee

Shinwho Kwun

Student, Vanderbilt University, Blair School of Music, Nashville, Tennessee

Ashley Suh

Student, Department of Medicine, Health, and Society, Vanderbilt University, Nashville, Tennessee

Sandra Sanchez-Roige, PhD

Associate Professor, Department of Psychiatry, University of California, Oakland, California; Vanderbilt University Medical Center, Division of Genetic Medicine, Nashville, Tennessee

Alvin D. Jeffery, PhD

Assistant Professor, Department of Biomedical Informatics, Vanderbilt University School of Nursing, Vanderbilt University Medical Center, Nashville, Tennessee

David C. Samuels, PhD

Associate Professor, Department of Molecular Physiology and BioPhysics, Vanderbilt University School of Medicine, Vanderbilt Genetics Institute, Nashville, Tennessee

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