ArticleAnnals of family medicine2020
Financing Buprenorphine Treatment in Primary Care: A Microsimulation Model.
Article in Annals of family medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed, 11 citations in OpenAlex.
- Article
- Expanding buprenorphine prescribing in primary care: a qualitative study of the experiences of primary care providers and nurse care managers participating in the New York City buprenorphine nurse care manager initiative.Harm reduction journal · 2025Article
- Implementation of an office-based addiction treatment model for Medicaid enrollees: A mixed methods study.Journal of substance use and addiction treatment · 2024Article
- Financial Sustainability of Novel Delivery Models in Behavioral Health Treatment.The journal of mental health policy and economics · 2023Review
- Review
- Financial sustainability of payment models for office-based opioid treatment in outpatient clinics.Addiction science & clinical practice · 2021Review
- Financial models used to embed registered nurses in primary health care settings in the United States: A scoping review.Nursing outlookArticle
- Characteristics, work environments, and rates of burnout and job dissatisfaction among registered nurses in primary care.Nursing outlookArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWe sought to determine the financial impact to primary care practices of alternative strategies for offering buprenorphine-based treatment for opioid use disorder.
methodsWe interviewed 20 practice managers and identified 4 approaches to delivering buprenorphine-based treatment via primary care practice that differed in physician and nurse responsibilities. We used a microsimulation model to estimate how practice variations in patient type, payer, revenue, and cost across primary care practices nationwide would affect cost and revenue implications for each approach for the following types of practices: federally qualified health centers (FQHCs), non-FQHCs in urban high-poverty areas, non-FQHCs in rural high-poverty areas, and practices outside of high-poverty areas.
resultsThe 4 approaches to buprenorphine-based treatment included physician-led visits with nurse-led logistical support; nurse-led visits with physician oversight; shared visits; and solo prescribing by physician alone. Net practice revenues would be expected to increase after introduction of any of the 4 approaches by $18,000 to $70,000 per full-time physician in the first year across practice type. Yet physician-led visits and shared medical appointments, both of which relied on nurse care managers, consistently produced the greatest net revenues ($29,000-$70,000 per physician in the first year). To ensure positive net revenues with any approach, providers would need to maintain at least 9 patients in treatment, with a no-show rate of <34%.
conclusionsUsing a simulation model, we estimate that many types of primary care practices could financially sustain buprenorphine-based treatment if demand and no-show rate requirements are met, but a nurse care manager-based approach might be the most sustainable.
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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.