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. 2023 Aug:2:100007.
doi: 10.1016/j.xjmad.2023.100007. Epub 2023 Jun 22.

Diagnosing major depressive disorder and substance use disorder using the electronic health record: A preliminary validation study

Vinod Rao  1 , Sylvia Lanni  1 , Amy M Yule  2 , Maura DiSalvo  1 , Mira Stone  1 , Amy F Berger  1 , Timothy E Wilens  1
Affiliations

Diagnosing major depressive disorder and substance use disorder using the electronic health record: A preliminary validation study

Vinod Rao et al. J Mood Anxiety Disord. 2023 Aug.

Abstract

Background: One mechanism to examine if major depressive disorder (MDD) is related to the development of substance use disorder (SUD) is by leveraging naturalistic data available in the electronic health record (EHR). Rules for data extraction and variable construction linked to psychometrics validating their use are needed to extract data accurately.

Objective: We propose and validate a methodologic framework for using EHR variables to identify patients with MDD and non-nicotine SUD.

Methods: Proxy diagnoses and index dates of MDD and/or SUD were established using billing codes, problem lists, patient-reported outcome measures, and prescriptions. Manual chart reviews were conducted for the 1-year period surrounding each index date to determine (1) if proxy diagnoses were supported by chart notes and (2) if the index dates accurately captured disorder onset.

Results: The results demonstrated 100% positive predictive value for proxy diagnoses of MDD. The proxy diagnoses for SUD exhibited strong agreement (Cohen's kappa of 0.84) compared to manual chart review and 92% sensitivity, specificity, positive predictive value, and negative predictive value. Sixteen percent of patients showed inaccurate SUD index dates generated by EHR extraction with discrepancies of over 6 months compared to SUD onset identified through chart review.

Conclusions: Our methodology was very effective in identifying patients with MDD with or without SUD and moderately effective in identifying SUD onset date. These findings support the use of EHR data to make proxy diagnoses of MDD with or without SUD.

Keywords: Depression; Electronic health record; Methods; Substance use; Validation.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests; Timothy Wilens reports financial support was provided by National Institute on Drug Abuse. Amy Yule reports financial support was provided by National Institute on Drug Abuse, the Doris Duke Charitable Foundation’s COVID-19 Fund to Retain Clinical Scientists collaborative grant program through support from the John Templeton Foundation, and the National Center for Advancing Translational Sciences, National Institute of Health, through the Boston University Clinical and Translational Science Institute. She also has funding for clinical program development from the Jack Satter Foundation. Timothy Wilens reports relationships with US Minor/Major League Baseball, Gavin Foundation and Bay Cove Human Services that include: consulting or advisory. Amy Yule reported relationships with Gavin House and Bay Cove Human Services and the American Psychiatric Association’s Providers Clinical Support System Sub-Award that include: consulting or advisory. Timothy Wilens has a licensing agreement with Ironshore (BSFQ Questionnaire) and 3D Therapeutics. Corresponding author co/edited books: ADHD in Adults and Children (Cambridge University Press), Straight Talk About Psychiatric Medications for Kids (Guilford Press), An Update on Pharmacotherapy of ADHD (Elsevier Press) -T.W.

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