Our Take
Hospitals are losing money not because denials are increasing in volume, but because payers now use AI to predict which denials will go unchallenged—and target those deliberately.
Why it matters
As payer denial rates climb (11% of claims in 2023 vs. 8% in 2021), the economics of appeal have shifted. Hospitals paying $57 per denial worked cannot afford to stay reactive when insurers deploy predictive models to maximize revenue capture through low-effort, high-success denials.
Do this week
Revenue cycle director: Audit your denial data by appeal rate and recovery yield this month so you can identify which payer denial categories go unchallenged due to cost, not merit.
Payers shift from rule-based to behavior-based denial strategy
Insurance companies historically denied claims based on coding, medical necessity, or policy compliance. Today, they layer AI analytics on top of claims history to predict provider behavior. Payers now score denials by likelihood of appeal, historical overturn rates, and even whether an underpayment will stay below internal review thresholds.
The American Medical Association reports that claim denials rose to 11% in 2023 from 8% in 2021 (per the AMA), translating to roughly 110,000 unpaid claims per average health system annually. The cost to work a single denial increased from $44 in 2022 to $57 in 2023 (per Becker's Hospital Review), collectively consuming over $20 billion in provider effort yearly (per MGMA polling).
Payers have access to years of provider-specific data: which denial codes hospitals appeal most, which service lines see low appeal volume due to staffing constraints, and which underpayments consistently go unnoticed. When fed into AI decision engines, this becomes a "denial risk score" that prioritizes claims unlikely to be challenged. A denial succeeds not because it is correct, but because it is inconvenient for the provider to contest.
Revenue loss becomes invisible when denials are designed to avoid scrutiny
The danger for hospitals is that revenue erosion from this tactic does not always appear as a spike in denial volume. Denial rates can stay flat while the composition of denials shifts toward low-appeal, high-success cases. Individual claims look immaterial; collectively, the impact compounds.
Hospital operating margins sit at 1.2% (per recent quarterly data), leaving no margin for error. Hospitals facing $57-per-denial costs and constrained revenue cycle teams have genuine financial incentives to abandon low-dollar claims. Payers understand this calculus and exploit it. The revenue you don't see is the revenue you lose.
Use analytics to spot payer patterns and reset contract terms
Leading providers are beginning to analyze denials through a different lens: not just reason codes and volume, but cost to appeal, probability of recovery, and true financial impact. The questions shift from "Why was this denied?" to "Why does this denial persist?" and "Which payers show patterns of denials that go unchallenged?"
This data-driven approach serves two purposes. First, it exposes payer behavior patterns that individual claims cannot reveal. Second, it gives revenue cycle teams ammunition for contract renegotiation. When providers can show statistically defensible patterns rather than anecdotal complaints, payer conversations change.
Hospitals should prioritize identifying denial categories with the lowest appeal rates and highest underpayment volume, then evaluate whether those denials are actually valid. Similarly, track which payers issue partial payments or "soft denials" that bypass formal workflows, and measure how often your teams choose not to appeal due to effort, not merit. This visibility becomes the foundation for targeted appeals, contract discussions, or formal escalation.