The study, published on 20 September 2026 as a research letter in volume 318 of the journal, takes advantage of a uniquely transparent data resource. Rather than relying on insurance claims, which are often proprietary and difficult to obtain, the team drew on publicly accessible provider-level data hosted by the U.S. Department of Health and Human Services, specifically the Medicaid provider spending datasets available through the department’s open data portal. Because the analysis used only publicly available provider-level information containing no identifiable patient data, the authors note that institutional review board approval was not required, and the work was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

The technical logic behind the approach is worth unpacking. Medicaid, the joint federal-state health insurance program, operates differently across states, and a substantial share of beneficiaries are enrolled in managed care plans rather than traditional fee-for-service arrangements. Fee-for-service data, in which providers bill the program directly for each service rendered, offer a consistent signal of whether a given physician is actually treating Medicaid patients. By tracking participation among surgeons who perform Mohs micrographic surgery, identified through billing for the procedure, the researchers could construct a picture of access trends over time, capturing whether the pool of surgeons willing to accept Medicaid beneficiaries is shrinking, growing, or holding steady.

Why does this matter clinically? Mohs micrographic surgery is a tissue-sparing technique most often used for nonmelanoma skin cancers, particularly basal cell carcinoma and squamous cell carcinoma located on high-risk areas such as the face, ears, and hands. The procedure involves the sequential removal of thin layers of tissue, each examined microscopically at the bedside while the patient waits, allowing the surgeon to map exactly where tumor cells remain. This real-time margin assessment maximizes cure rates while minimizing the removal of healthy tissue, which is why it is favored for tumors in cosmetically and functionally sensitive sites. Skin cancer is among the most common cancers in the United States, and access to this procedure is therefore not a niche concern but a mainstream issue in oncologic dermatology.

The new study does not stand in isolation. It builds on a growing body of literature documenting disparities in dermatologic care for Medicaid beneficiaries. Prior work cited by the authors includes a 2020 study in the Journal of the American Academy of Dermatology by Mazmudar and colleagues, which compared dermatologist appointment access and waiting times across insurance types and found that Medicaid patients faced meaningful barriers to securing care. A 2023 study by Sharma and colleagues examined nonmelanoma skin cancer and the utilization of Mohs micrographic surgery specifically among Medicaid patients, highlighting questions about whether this population receives guideline-concordant surgical treatment at the same rate as privately insured patients.

Perhaps most directly relevant is a 2023 analysis by Beltrami, Hooper, Kodumudi, and colleagues, also published in the Journal of the American Academy of Dermatology, which investigated the association between state-specific reimbursement rates and Medicaid acceptance for Mohs micrographic surgery. That work pointed toward a familiar economic mechanism: when states pay less for a procedure, fewer specialists are willing to accept that insurance. A companion 2022 study by the same group characterized the physicians who do accept Medicaid for Mohs surgery, beginning to sketch a profile of the provider workforce serving this population. The new research letter extends this line of inquiry from static snapshots to longitudinal trends, asking not just who accepts Medicaid today but how participation has shifted across the recent past.

The workforce dimension adds another layer of urgency. A 2025 cross-sectional analysis by Ahn, Yu, Scott, and colleagues sought to define the Mohs micrographic surgery workforce itself, using billing data for the primary tissue-processing code from 2015 to 2020 to estimate how many surgeons perform the procedure nationally. Understanding the size and distribution of that workforce is a prerequisite for understanding access: if the number of Mohs surgeons is limited and only a fraction accept Medicaid, the effective supply of care available to beneficiaries may be far smaller than headline counts of providers suggest. The Mount Sinai team’s trend analysis speaks directly to this concern by measuring the dynamic component, participation, rather than the static component, headcount.

Methodologically, the study is a research letter, a compact format that journals use to disseminate timely findings without the full apparatus of an original article. The authors report that all three contributed to writing the manuscript, with O’Hagan preparing the two figures that accompany the letter. The team declared no conflicts of interest and reported no external funding, and the corresponding author is Lewin, whose department, the Kimberly and Eric J. Waldman Department of Dermatology at Mount Sinai, sits at the intersection of clinical practice and health services research in New York City, a market where insurance dynamics and specialist access are under perpetual scrutiny.

The policy stakes of this line of research are considerable. Medicaid enrollment in the United States has fluctuated dramatically in recent years, swelling during the pandemic-era continuous enrollment period and contracting as states resumed eligibility redeterminations. Each swing shifts the composition of the insured population and, by extension, the demand placed on specialists. If participation in fee-for-service Medicaid among Mohs surgeons is declining even as enrollment rises, the mismatch could translate into longer travel distances, longer waits, or transitions to less tissue-sparing treatments for beneficiaries, outcomes with direct implications for cancer control in a vulnerable population. Reimbursement policy, scope-of-practice debates, and workforce training all intersect here, and granular participation data give policymakers a lever for evaluating interventions such as rate increases or network adequacy requirements.

For readers following the science of health equity, the study is a reminder that access to advanced surgical care is shaped as much by administrative and economic structures as by biology. The technique itself, developed decades ago and refined through generations of surgeons, offers cure rates that few oncologic procedures can match. Whether that benefit reaches patients on public insurance depends on datasets like the ones this team mined, on researchers willing to ask unglamorous questions about billing and participation, and on the willingness of states to align reimbursement with the realities of surgical practice. The full article, including the figures charting participation trends, is available in the Archives of Dermatological Research, and the underlying data remain publicly accessible for other investigators to interrogate, replicate, and extend.

Subject of Research: Trends in fee-for-service Medicaid participation among Mohs micrographic surgery providers in the United States

Article Title: Trends in fee-for-service medicaid participation in Mohs micrographic surgery

Article References: Trends in fee-for-service medicaid participation in Mohs micrographic surgery. (n.d.). https://doi.org/10.1007/s00403-026-04876-1

Image Credits: AI Generated

DOI: 10.1007/s00403-026-04876-1

Keywords: Mohs micrographic surgery, Medicaid, dermatology, health policy, skin cancer, healthcare access, insurance participation, health disparities, reimbursement, workforce, fee-for-service, nonmelanoma skin cancer

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