Healthcare organizations today are running on thinner margins than ever. According to MGMA’s October 2025 DataDive analysis, nearly half of medical group leaders report declining operating margins per FTE physician compared to last year, driven by stagnant payer reimbursement, rising staffing costs, and ongoing claim denials.
In that environment, even small administrative inefficiencies have outsized consequences.
Payer enrollment, the process that determines when a provider can bill for care, is a prime example. Each extra week in processing can mean thousands of dollars in delayed revenue for an organization, and yet the greater challenge isn’t just duration, but rather, inconsistency.
To better understand these variations, Medallion analyzed over 64K enrollment records. What we found is that not all delays are created equal — and understanding where and why timelines diverge is the opportunity to build a more predictable, equitable system for providers and patients alike.
Payer enrollment isn’t one process — it’s 50+ different ones
Payer enrollment timelines vary significantly by state and even more within states. Different Medicaid documentation rules, liability-insurance minimums, and requirements for background checks or site visits make each jurisdiction its own maze. Commercial payers add another layer of complexity with their own submission standards and review cycles.
Part of our analysis uncovered that this creates a patchwork system where geography can dictate operational predictability.
Two providers in the same state, even within the same city, can experience completely different timelines depending on which payer they’re working with. In some regions, 30-day turnarounds are routine; in others, six months is not uncommon.
And with such dramatic differences, the unpredictability is more than just a back-office frustration. It has measurable financial and human impact.
When a provider isn’t fully enrolled, they can’t bill or see insured patients. In high-delay states like South Dakota and Michigan, where weighted median enrollment times exceed 90 days, the average deferred revenue per provider surpasses $200,000.
For small practices, one prolonged enrollment can derail a launch. For hospitals and systems, dozens of pending providers translate into millions in deferred reimbursements and delayed access for patients. The result is a system that inadvertently penalizes care expansion in the very places that need it most.
How do you bend the cost curve on variation?
If margin pressure defines the moment, then consistency defines the opportunity. The variation in payer enrollment timelines doesn’t just slow care — it compounds cost. Every additional week of unpredictability adds administrative labor, deferred revenue, and rework that ripples across entire networks.
Fundamentally, the only way to bend the cost curve on this variation long-term is through automation, accuracy, and accountability at scale. These are the forces that structurally change what it costs to get a provider ready to see patients, and providers are ready for it. According to this year’s Philips Future Health Index poll, 74% percent of clinicians believe AI can expand access to care and create smarter workflows.
That means:
- Reducing manual work across enrollment workflows through intelligent automation — extracting, validating, and submitting data without repetitive touchpoints.
- Building accuracy into every step with systems that learn payer- and state-specific rules, preventing downstream denials and resubmissions before they happen.
- Scaling operational performance transparently, with measurable turnaround targets (e.g., accelerate provider onboarding, reducing credentialing and enrollment cycles from 90–120 days to under two hours) and continuous monitoring to keep every payer and provider aligned on outcomes.
Automation minimizes overhead. Accuracy eliminates rework. Accountability ensures performance is maintained as networks grow. Together, these levers convert enrollment efficiency from a reactive cost center into a proactive source of stability and speed.
True efficiency comes from shared standards, not siloed effort
Many healthcare organizations are trying to tackle enrollment inefficiencies on their own, and their efforts are well-intentioned. Operations teams are using manual tracking systems or layering new point solutions onto legacy workflows. Many health systems use four or more disconnected systems to manage back-office work like enrollment.
But these incremental fixes rarely scale.
Labor costs have surged 36.4% since 2019, outpacing general inflation by more than 13 points, according to a New York State Hospitals report. For most organizations, that means every additional FTE comes at a higher cost, yet the underlying processes remain just as broken. More people in the process doesn’t guarantee faster outcomes, and in many cases, it can amplify variation rather than reducing it.
In an environment this complex, the path to predictability lies in building toward shared standards. Emerging collaborative frameworks that align payers, providers, and technology partners—especially around credentialing and enrollment — offer a promising opportunity to reduce administrative burden, accelerate timelines, and improve data integrity.
By combining automation, shared accountability, and deep domain expertise, these models help healthcare organizations shift away from reactive workflows toward more scalable, coordinated operations.
(Editor’s note: Medallion helps lead this work through initiatives like CredAlliance™, a collaborative industry framework to standardize credentialing and enrollment data exchange across payers and providers.)
What healthcare leaders need to look at differently
Variation in payer enrollment is both an administrative issue and an economic signal. It reveals where systems are stretched, where inefficiencies concentrate, and where access to care slows down.
Healthcare leaders need to start treating enrollment timelines as a strategic performance metric, not a back-office statistic. Predictability — when a provider can start seeing patients, when a claim can be submitted, when revenue can flow — has become a competitive advantage.
Understanding those differences, and acting on them, is the first step toward structural improvement.
Explore the data behind this analysis in the U.S. Geography of Enrollments report to see how your state compares, and where predictability can make the biggest financial and operational impact.
