_.png)
The $48B Blind Spot in Healthcare Revenue Operations
- Adam Peddicord
- Apr 28
- 8 min read
Healthcare doesn’t have a revenue problem. It has a Revenue Operations identity crisis.
Two completely different systems are running in parallel. Almost no one is accountable for connecting them.
Ask a SaaS executive what Revenue Operations is, and you’ll get a confident answer in under thirty seconds: aligning sales, marketing, and customer success around a unified revenue model. Pipeline forecasting. Lead routing. CRM hygiene. Net revenue retention.
Ask a hospital CFO the same question, and you’ll get a longer pause. Then a description of the Revenue Cycle: scheduling, eligibility, prior authorization, charge capture, coding, claims, denials, collections.
Both answers are correct. Both are also incomplete.
Healthcare doesn’t have one Revenue Operations function. It has two. And they barely talk to each other.
And the gap between them is exactly where healthcare’s next competitive advantage is hiding.
Three questions I keep hearing from healthcare operators, AI vendors, and clinical leaders:
Does RevOps actually exist in healthcare, and if so, where does it live?
What are operators and administrative leaders actually complaining about?
How is AI rewriting this discipline in real time?
Let's get into it.
Healthcare RevOps: two disciplines, one blindspot
Here's how that actually shows up in practice:
Track A: Healthcare Technology Companies (SaaS-style RevOps)
If you work at a digital health startup, an EHR vendor, an RCM platform, a life sciences AI company, or a healthcare cybersecurity firm, you live in a familiar world. Your RevOps team unifies marketing, sales, and customer success around a shared pipeline, a shared CRM, and shared revenue metrics. RevOps as a discipline was championed by analyst firms around 2018 and now spans roles like Director of Revenue Operations, VP of Revenue Operations, and Chief Revenue Officer. By 2026, 75% of high-growth organizations are expected to adopt a RevOps model, with reported benefits like a 30% reduction in go-to-market expenses.
In this track, RevOps typically reports to the CRO, CFO, or COO depending on company maturity. It's funded as a strategic investment in growth, and it's increasingly AI-native.
Track B: Healthcare Provider Organizations (Revenue Cycle Management)
If you work at a hospital, health system, physician group, ASC, or specialty practice, "Revenue Operations" probably isn't even in your org chart. Instead, you have a Revenue Cycle. It's run by a Director, VP, or SVP of Revenue Cycle who almost always reports to the CFO. The healthcare revenue cycle is generally broken into three stages: front-end (scheduling through check-in), mid-cycle (capturing and coding the patient encounter), and back-end (post-bill workflows).
This is not a small operation. The U.S. healthcare revenue cycle management market was valued at $65 billion in 2025 and is projected to reach $196 billion by 2035, growing at an 11.6% CAGR. In 2025 alone, the American Hospital Association reported that hospitals collectively spent about $43 billion just to collect payments from insurers, with the average hospital employing 64 administrative and billing staff to handle the workload.
Why this matters
These two tracks evolved separately, but they're now converging. Value-based care, patient consumerism, and AI-driven automation are forcing hospitals to think more like SaaS companies (lifecycle thinking, customer experience, NPS, retention). Meanwhile, healthcare technology vendors increasingly need to understand the operational realities of RCM workflows to sell into provider organizations.
If you're building, buying, or running anything that touches patient revenue, you need fluency in both dialects. The leaders who understand this are the ones who'll navigate the next five years intact.
Here’s where this stops being theoretical and starts costing real money.
The pain points: what operators are actually saying
I've spent the last two years in conversations with revenue cycle directors, COOs, CMIOs, and practice administrators. The frustrations aren't subtle. Here's what consistently surfaces, backed by the data.
Denials aren't operational anymore. They're existential.
Kodiak Solutions' inaugural “State of the healthcare revenue cycle” report (built on data from more than 2,300 hospitals and 350,000 physicians) found that net revenue leakage rose roughly 25% in 2025 compared with 2024, with affected providers losing more than $48 billion in net revenue to final denials and uncollected patient balances. Median final denial rates ticked up from 2.5% to 2.7%, but the more telling shift was in clinical denials: rates for lack of prior authorization or medical necessity drove nearly the entire increase. Medicare Advantage final denial rates were more than double those of traditional Medicare (5.0% versus 1.9%).
Here's the kicker that revenue cycle leaders won't say in public but tell me privately: payer behavior has overtaken internal staffing as the top-cited threat to revenue growth. The job has shifted from operational excellence to adversarial negotiation.
Prior authorization is breaking workflows and patient care simultaneously
The 2024 AMA Prior Authorization Physician Survey (fielded among 1,000 practicing physicians) produced data that should be required reading for every health system board. Among the findings: 93% of physicians said prior authorization delays patient care; 82% said it sometimes leads patients to abandon a recommended course of treatment; 94% said it negatively affects clinical outcomes; and 29% reported that prior authorization had caused a serious adverse event for a patient in their care, including hospitalization, disability, or death. Physicians and their staff complete an average of 39 prior authorizations per week, consuming roughly 13 hours of work. Forty percent of practices have hired staff dedicated exclusively to prior authorization.
Every prior auth delay is both a revenue event and a clinical event. Yet most organizations still treat it as a back-office task.
Operators are running out of margin to make mistakes
The American Hospital Association's 2025 Cost of Caring report lays out the financial pressure in unambiguous terms. Total hospital expenses grew 7.5% in 2025 (more than twice the rate of growth in hospital prices), driven by labor costs (up 5.6%), supplies (up 9.9%), and drug spending (up 13.6%). Workforce remains the single largest cost category, accounting for roughly 56% of hospital spending. Hospitals collectively spent nearly $18 billion in 2025 fighting claims that payers initially denied.
Underneath those headline numbers, most hospitals are operating on margins at or near breakeven, leaving virtually no buffer for avoidable denials, coding errors, or missed eligibility checks.
Clinical staff are paying the tax
This is the one operators care about most but talk about least: revenue cycle dysfunction shows up in physician burnout. The Commonwealth Fund's October 2025 issue brief on administrative burden in primary care frames the problem clearly. Primary care physicians face mounting documentation demands, including the redocumentation of chronic conditions every year for HCC risk scoring, even for diagnoses like leg amputations that don't change. The brief connects administrative burden directly to demoralization, burnout, and the worsening primary care workforce shortage.
When I sit down with health system leaders, the conversation almost always lands here: the revenue cycle is no longer an isolated finance function. It's a clinical workforce problem, a patient experience problem, and a strategic survival problem all at once.
And this is where most leaders are already behind.
AI in healthcare RevOps: already restructuring the discipline
This is the section I keep getting asked about most, and the data has moved fast. If your understanding of AI in healthcare revenue operations is more than 12 months old, it's wrong.
Adoption has crossed the chasm
The HFMA/AKASA Revenue Cycle Intelligence Report (fielded among 519 hospital CFOs and revenue cycle leaders) found that 80% of health systems are exploring, piloting, or implementing generative AI tools for RCM in 2025, a relative jump of roughly 38% in less than two years. Among the largest health systems, 64% are actively piloting or implementing GenAI solutions, while only 20% of organizations with revenues between $500 million and $1 billion have reached the same stage.
What's actually being deployed
The shift from “AI assistance” to agentic AI (systems that execute tasks autonomously with human oversight) is the headline story of 2025–2026. Specifically:
Autonomous coding. The market is moving from Computer-Assisted Coding (CAC) to fully autonomous coding, with vendors reporting measurable revenue uplift, denial reduction, and A/R improvement among early adopters.
Predictive denial prevention. AI models flag claims likely to be denied before submission, then route them for documentation fixes upstream.
Agentic prior authorization and eligibility. AI agents are now handling end-to-end prior auth submissions and status tracking with payer-specific intelligence.
The economics are eye-watering
Deloitte's 2024 Life Sciences and Health Care Generative AI Outlook Survey (which specifically interrogated AI sentiment among healthcare leaders) found that 92% see promise in GenAI for improving operational efficiencies and 65% expect quicker decision-making from it. 75% of leading healthcare companies are already experimenting with or planning to scale GenAI across the enterprise.
Zooming out: a widely cited NBER working paper by Sahni, Stein, Zemmel, and Cutler estimated that wider adoption of AI in U.S. healthcare could generate annual savings of 5–10% of total healthcare spending, or roughly $200 billion to $360 billion in 2019 dollars, without compromising quality or access. These aren't pie-in-the-sky figures. They're use-case-grounded estimates built from specific administrative and operational AI applications already feasible with today's technology.
But the dark side is real
Two things keep me up at night about this trend:
Payers are weaponizing AI faster than providers are deploying it. Health systems are still scaling pilots while payers are running real-time claims adjudication and denial generation at machine speed.
Cost and governance are the real bottlenecks, not capability. Many health systems remain in the early stages of adoption, citing cost and budget constraints as the largest obstacles. Add to that emerging state-level AI regulation, HIPAA implications, vendor risk, and the lack of standardized governance frameworks. The capability is here. The operating discipline isn't.
If you zoom out, this isn’t about automation. It’s about who controls the revenue intelligence layer: providers or payers.
What this means if you lead a healthcare organization
A few things I'd push every healthcare operator, CFO, and digital health leader to internalize:
The line between "revenue cycle" and "revenue operations" is dissolving. The disciplines were separated by accident of industry vocabulary, not by underlying logic. The leaders who unify them (pulling in lifecycle thinking, patient experience, predictive analytics, and AI-native automation) will widen the gap on competitors who treat RCM as a back-office cost center.
You cannot AI your way out of broken upstream processes. Every AI vendor will tell you their tool delivers transformative ROI. They're often right, and often wrong, depending entirely on whether you've done the unsexy work of standardizing workflows, cleaning data, and aligning ownership before deployment. The hospitals that win with AI in 2026 are the ones that won with process discipline in 2024.
Vendor validation needs to grow up. I've sat through pitches where the gap between marketed capability and operational reality was a chasm. If you're a healthcare CFO or CIO evaluating AI RCM tools, you need a structured framework for vendor scrutiny: accuracy benchmarks, payer mix coverage, EHR integration depth, explainability, audit-readiness, and total cost of ownership. "Best in KLAS" is a starting point, not a decision.
The human element is not optional. Even the most capable autonomous systems need human-in-the-loop design, clear escalation paths, and clinical/financial team alignment. AI without an operating model around it just produces faster mistakes.
The bottom line
Revenue Operations in healthcare isn't one discipline. It's a converging set of functions (provider-side RCM, vendor-side RevOps, clinical operations, and AI infrastructure) that are being forcibly fused by economic pressure, payer behavior, and technology capability moving faster than most organizations can absorb.
The healthcare leaders who will thrive in the next three years aren't the ones with the biggest AI budgets or the deepest RCM benchmarking dashboards. They're the ones who've stopped treating "revenue" as a finance silo and started treating it as a system. One that touches every clinician, every patient interaction, every claim, and every payer relationship.
That's the work. And it's the work my team and I are doing every day with healthcare organizations trying to navigate it.
Until next time,
Comments