ArticleAmerican journal of epidemiology2021
Invited Commentary: Baby Steps to a Learning Mental Health-Care System-Can We Do the Work?
Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Comprehensive Model for Mental health Access and service use (CoMMA): A process model for technology-enhanced mental healthcare.Internet interventions · 2026Review
- Integrated Digital Mental Health Care: A Vision for Addressing Population Mental Health Needs.International journal of general medicine · 2024Article
- Formative evaluation prior to implementation of a brief treatment for posttraumatic stress disorder in primary care.Implementation science communications · 2023Article
- Comparative Effectiveness of Direct-Acting Antivirals for Posttraumatic Stress Disorder in Veterans Affairs Patients With Hepatitis C Virus Infection.American journal of epidemiology · 2022Article
- Coulombe et al. Respond to "Baby Steps to a Learning Mental Health-Care System".American journal of epidemiology · 2021Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There are an infinite number of small decisions to be made in routine clinical practice, and most will never be the subject of prospective research studies. Rather than making these decisions arbitrarily, learning health-care systems leverage experience represented by electronic health record data and other sources to inform decision-making and improve clinical practice. While this approach has been elusive in mental health, Coulombe et al. (Am J Epidemiol. 2021;190(7):1210-1219) use UK National Health Service data to evaluate a decision rule for antidepressant choice created using dynamic weighted survival modeling. Although the results are equivocal in this use case, the work suggests a path forward for data-driven decision-making in routine mental health care. Such approaches will be required to set the stage for a learning mental health care system.
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Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.