Why Payment Reform, Not Evidence, Is Holding Back Collaborative Mental Health Care

Mental health care in the United States has a paradox at its heart. Researchers have spent decades building and validating a model of depression and anxiety treatment that works, saves money, and stretches scarce psychiatric expertise further than anyone once thought possible. Yet the model, known as the Collaborative Care Model, remains a rarity in everyday clinical practice. A new perspective published in the Journal of General Internal Medicine by Jack J. Huang of Mass General Brigham, Ish Bhalla of WelbeHealth and Duke University, and Andrew D. Carlo of Yale School of Medicine argues that the obstacle is not scientific but financial: the way America pays for care has never matched the way the model creates value. And as primary care lurches toward value-based payment, the authors contend, a rare window is opening to fix that mismatch.

The Collaborative Care Model is a specific form of behavioral health integration in which primary care teams are joined by two additional roles: care managers, who coordinate and track treatment for patients with common psychiatric conditions, and psychiatric consultants, who advise on the harder cases without requiring every patient to secure an appointment with a psychiatrist. A registry tracks each patient’s symptoms over time, allowing the team to adjust treatment systematically rather than waiting for patients to return on their own. The approach emerged from randomized trials, most famously in the treatment of late-life depression, and has accumulated an unusually robust evidence base spanning clinical outcomes, implementation science, and health economics.

The numbers cited in the perspective are striking. Studies of the model report a return on investment of roughly six to one, driven largely by reductions in overall medical spending, not just psychiatric costs. Patients with poorly controlled behavioral health conditions, particularly those with chronic comorbidities, tend to generate higher total medical expenditures and worse outcomes, so treating depression and anxiety effectively in primary care ripples through the rest of the health system. Perhaps more remarkable is the workforce mathematics: by concentrating psychiatric expertise at the level of consultation rather than one-on-one visits, the model multiplies the impact of each psychiatrist’s effort by as much as seven times. In an era when the behavioral health workforce is limited and geographically concentrated, that leverage is not a luxury but a necessity.

So why has real-world adoption lagged so far behind the evidence? The authors point squarely at fee-for-service reimbursement, the dominant payment architecture in American medicine. In 2017, the Centers for Medicare and Medicaid Services created billing codes specifically designed to reimburse collaborative care and related behavioral health integration activities, a genuine step forward. But not all state Medicaid agencies or commercial payers have adopted those codes, reimbursement rates vary widely, and billing stipulations are inconsistent across payer types and practice settings. The codes themselves are administratively demanding, requiring clinicians to track the minutes spent delivering collaborative care each month and then determine which codes to bill at month’s end. That complexity alone deters many practices from starting.

The deeper problem, however, is structural. Under fee-for-service, the primary care organization must front the investment required to implement the model, hiring care managers, building registries, and reorganizing workflows, while the savings from reduced total cost of care flow to the payer. Behavioral health, meanwhile, competes for investment capital against more lucrative fee-for-service revenue generators, often procedures. In other words, the party that pays the costs is not the party that reaps the returns. The authors argue that simply expanding the billing codes across payers, while worthwhile, is unlikely to be sufficient to drive adoption at the scale the evidence justifies.

The opportunity, they suggest, lies in the ongoing migration of primary care into value-based payment arrangements: risk-bearing provider organizations, value-based primary care companies, capitated programs for beneficiaries dually eligible for Medicare and Medicaid, and demonstration models from the CMS Innovation Center aimed at medically complex patients. To organize their recommendations, the authors use the framework of alternative payment models developed by the Health Care Payment Learning and Action Network, which sorts payment arrangements into four categories of increasing provider accountability. Category 1 is traditional fee-for-service; category 2 adds links to quality and value, such as pay-for-performance; category 3 introduces shared savings and shared risk; and category 4 is full population-based payment.

For each stage, the authors propose a tailored incentive strategy. In pure fee-for-service settings, payers should universally adopt the collaborative care codes, offer more favorable fee schedules with reduced administrative burden, particularly for medically complex populations and youths, and consider upfront infrastructure payments to offset implementation costs. In pay-for-performance arrangements, those measures would be supplemented by incorporating the model as a structural quality measure and adding behavioral health outcome metrics such as benchmarks for treatment response or remission. In shared savings and shared risk arrangements, the recommendation is a hybrid: maintain some fee-for-service reimbursement while allowing providers to share downstream savings, and remove the model’s codes from primary care capitation fee reduction lists, at least during early implementation, because returns may not materialize until the second year or beyond.

At the most advanced stage, full population-based payment, providers theoretically capture the savings themselves, reducing the need for separate fee-for-service reimbursement. But the authors draw a technical distinction here: the return on investment in collaborative care comes substantially through medical cost savings, not merely behavioral health savings, so the inherent incentive is strongest under comprehensive population-based payment rather than condition-specific arrangements. Even in these advanced models, they caution, implementation incentives remain warranted because the financial returns take time to realize. Across all four categories, the authors add cross-cutting policy recommendations: minimizing patient cost-sharing, harmonizing billing stipulations across payers to reduce administrative burden, pushing all state Medicaid agencies to adopt the codes, and providing technical assistance, information technology support, and staffing help, as North Carolina and other states have begun to do.

What makes the argument timely is the convergence of pressures on primary care. Value-based arrangements reward outcomes and efficiency, which is precisely what collaborative care delivers, yet the perspective notes a perverse detail: in many accountable care organizations, the model’s fee-for-service codes appear on lists of primary care capitation fee reductions, cutting that payment by as much as one hundred percent. Despite this, the authors maintain that collaborative care remains the most advantageous behavioral health integration model available, given its demonstrated success across research and real-world settings in treatment access, clinical outcomes, and return on investment. The payment architecture, in their view, is the last remaining bottleneck, and it is one that policymakers can address with tools that already exist.

The stakes extend well beyond billing mechanics. Untreated depression and anxiety impose costs throughout the health system, from worsened chronic disease control to avoidable hospitalizations, and the shortage of psychiatric clinicians means that simply training more providers cannot close the access gap quickly enough. The authors’ segmented approach treats payment reform not as a single lever but as a sequence of calibrated ones, matched to where each provider organization actually sits on the road from fee-for-service to full accountability for population health. If they are right, aligning incentives with the evidence could turn a proven but underused model into the default way American primary care treats the mind, expanding access to effective behavioral health care at a scale the current system has never achieved.

Subject of Research: Payment policy and adoption of the Collaborative Care Model for behavioral health integration in value-based primary care

Article Title: Evidence-Based Behavioral Health in Value-Based Primary Care: Aligning Incentives to Accelerate Adoption of Collaborative Care

Article References: Huang, J. J., Bhalla, I., & Carlo, A. D. (2026). Evidence-Based Behavioral Health in Value-Based Primary Care: Aligning Incentives to Accelerate Adoption of Collaborative Care. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10868-8

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10868-8

Keywords: Collaborative Care Model, behavioral health integration, value-based payment, primary care, fee-for-service, alternative payment models, return on investment, psychiatry workforce, Medicaid, health policy, depression treatment, shared savings