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Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records

Molecular Psychiatry (2024)Cite this article

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Abstract

Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

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Fig. 1: Predictors of high negative outcome risk in the test sample.
Fig. 2: Predictors of being optimized by psychotherapy only.

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Data availability

No. Data were obtained through a nontransferable data use agreement with the Veterans Health Administration.

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Acknowledgements

Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Veterans Health Administration.

Funding

The research reported here was funded by the U.S. National Institute of Mental Health, Grant number R01MH121478, and by the VA Center of Excellence for Suicide Prevention, Canandaigua VA Medical Center.

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Authors and Affiliations

  1. Department of Health Care Policy, Harvard Medical School, Boston, MA, USA

    Nur Hani Zainal, Sarah M. Gildea, Irving Hwang, Howard Liu, Maria V. Petukhova, Nancy A. Sampson & Ronald C. Kessler

  2. Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, FL, USA

    Robert M. Bossarte

  3. Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA

    Chris J. Kennedy

  4. Center of Excellence for Suicide Prevention, Canandaigua VA Medical Center, Canandaigua, NY, USA

    Howard Liu

  5. Department of Statistics, University of Washington, Seattle, WA, USA

    Alex Luedtke

  6. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Alex Luedtke

  7. National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA

    Brian P. Marx

  8. Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA

    Brian P. Marx

  9. Center for Clinical Management Research, VA Ann Arbor Health Care System, Ann Arbor, MI, USA

    Edward P. Post

  10. Department of Medicine, University of Michigan Medical School, Ann Arbor, MI, USA

    Edward P. Post

  11. Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington, VT, USA

    Eric L. Ross

  12. Graduate School of Business, Stanford University, Stanford, CA, USA

    Erik Sverdrup & Stefan Wager

  13. Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Brett Turner

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Contributions

RCK and RMB conceptualized and designed the study. RCK and NHZ drafted the manuscript. HL and ES led the statistical analysis. RMB obtained funding. CJK, RCK, AL, ES, and SW provided administrative, technical, and material support. RCK, AL, NAS, ES, and SW supervised the study. All authors were involved in the acquisition, analysis, or interpretation of data. All critically revised the final manuscript draft and approved the submission.

Corresponding author

Correspondence to Ronald C. Kessler.

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Competing interests

In the past 3 years, RCK was a consultant for Cambridge Health Alliance, Canandaigua VA Medical Center, Holmusk, Partners Healthcare, Inc., RallyPoint Networks, Inc., and Sage Therapeutics. He has stock options in Cerebral Inc., Mirah, PYM, Roga Sciences and Verisense Health. The remaining authors declare no competing interests.

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Zainal, N.H., Bossarte, R.M., Gildea, S.M. et al. Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records. Mol Psychiatry (2024). https://doi.org/10.1038/s41380-024-02500-0

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