ArticleNpj mental health research2026
A large-scale evaluation of provider-patient matching in an employer-sponsored mental health program.
Article in Npj mental health research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Many patients do not improve during their first round of psychotherapy, partly due to variability in the quality of the patient-provider relationship. Matching patients to providers based on providers' historical performance with similar patients offers a proactive, data-driven solution. In a real-world retrospective cohort study, 24,303 participants using a mental health benefit (Spring Health) from 2021-2024 chose either matched therapists (i.e., based on providers' continuity of care, their historical patient-improvement percentile, and clinical alignment) or self-selected a therapist from a general list. Patients with depression using matched rather than self-selected therapists improved 8.5% faster (b = 0.12-point reduction on PHQ-9 per log-day, [95% CI: -0.15 to -0.09], p < 0.001) and were more likely to achieve reliable change (OR = 1.09 [1.05-1.14], p < 0.001), with similar results for anxiety and PTSD. Higher patient-provider fit scores predicted stronger therapeutic alliance (b = 0.05 [0.04-0.06], p < 0.001). Matching also reduced the total cost of care by 12.9% per reliable change and 10.8% per recovery. Thus, a data-driven patient-provider matching algorithm that is informed by providers' historical records with similar patients can provide modest but consistent acceleration of symptom improvement, increase clinical outcomes, and yield cost savings.
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