By Steve Palma, President & General Manager, Penstock
In American healthcare, money moves fast.
The Centers for Medicare & Medicaid Services (CMS) estimates that more than $5 trillion in claim payments, about 18% of the U.S. economy, move through the system each year. More than $100 billion of those payments are improper.
Despite years of effort, and better systems and smarter software, claim overpayments haven’t meaningfully declined.
Payment integrity teams used to work quietly in the back office — a “nice to have.” Today, the topic is debated in Congress and, for private insurers, in the boardroom, where it’s viewed as central to financial stability.
There is a moment every month when a health plan COO exhales. Claims have moved. Payments have cleared. The prompt-pay clock has been satisfied. On paper, the system is working.
But speed and accuracy are not the same thing.
Healthcare claims are typically required to be adjudicated within 30 days, with many health plans committed to paying claims much faster. That ticking clock shapes claims processing workflows, technology investments, staffing, and risk tolerance. It also imposes a structural ceiling on how deeply a claim can be reviewed for accuracy before money leaves the door.
Over the years, health plans have strengthened pre-payment payment integrity controls: automated edits, predictive models, real-time rules engines.
Now, with the rise of artificial intelligence, there’s renewed discussion about how much further pre-payment can go.
But even as pre-pay grows more sophisticated, its fundamental design remains oriented around speed and volume. No matter how advanced the rules engine, claims must still clear within regulatory timelines — which means the goal is triage, not investigation, and depth is always traded against throughput.
What pre-pay can’t reliably untangle within regulatory timelines are complex overpayments tied to benefit design, provider contract language, state carve-outs — situations where a state removes a benefit category from plan responsibility but billing behavior doesn’t immediately follow — and layered system configurations, where rules and edits added over time interact in ways no single layer was designed to anticipate. Those issues often surface only after payment, when a claim can be reviewed in full context, which requires more time than is allowed for pre-pay review.
This isn’t a failure of effort. It’s how the system is structured.
Complexity does not compress neatly into 30 days.
Why Post-Pay Auditing Improves Payment Accuracy
Post-payment auditing is often viewed as reactive, a way to recover dollars that slipped through.
But that framing misses its most important role.
Post-pay, when done deeply and defensibly, is not just about recovery. It is about causation. It offers something pre-pay cannot: time.
Time to review the claim in full context.
Time to align policy with contract language.
Time to understand how system logic behaved.
Time to ask, “Why did this happen?”
There’s a difference between identifying a one-off overpayment and identifying a systemic pattern.
“We found an overpayment” is an event.
“We found a pattern” is a turning point.
When post-pay uncovers root cause, it becomes the research-and-development engine behind pre-pay.
A validated pattern can drive system reconfiguration, provider education, policy clarification, and operational alignment across claims, IT, compliance, network management, and finance.
That’s the multiplier effect.
Recovery is the beginning. Prevention is the outcome.
How Post-Pay Analysis Prevents Recurring Claim Overpayments
When New York State carved pharmacy benefits out of Medicaid managed care into the NYRx program, the policy shift was clear. Billing behavior was not.
Specialty and home infusion pharmacies continued submitting certain services under the medical benefit, even after the state assumed responsibility. Claims were processed. Payments went out.
Only through post-pay analysis did a systemic pattern emerge: the plan was paying for services it was no longer contractually obligated to cover.
The response extended beyond recovery. Claims systems were reconfigured. Provider payment policies were clarified. Customer service teams were trained to respond consistently.
Millions of dollars were recovered. Millions more were prevented from leaking going forward. Forecast reliability improved because a recurring blind spot had been eliminated.
Without deep post-pay review, the issue would have continued, quietly compounding. The real impact was not just in the dollars recovered, but in the dollars no longer at risk.
Audit Quality, Explainability, and Financial Risk
Not all recoveries create value.
If a finding can’t withstand scrutiny, grounded clearly in plan policy and provider contracts, it creates friction instead of stability. Appeals rise. Teams spend time on rework. Confidence erodes.
Technology can surface anomalies. But many of the costliest overpayments live in the gray space between contracts, regulatory updates, and system configuration. Those patterns require expert interpretation.
For health plans, payment integrity findings influence reserves and forecasts. A poorly supported recovery becomes noise. A documented pattern that drives upstream correction becomes financial leverage.
Why Payment Integrity Matters for Financial Performance
Under medical loss ratio requirements and rate-setting pressure, health plans have limited levers to improve financial performance without reducing benefits or restricting access.
Payment integrity — done well — is one of the few.
Strong post-pay intelligence:
- Reduces financial surprises
- Surfaces structural issues early
- Strengthens confidence in reported results
- Supports more reliable forecasting
Poorly supported recoveries introduce compliance and operational risk.
Defensible findings introduce stability.
The Role of Post-Pay Auditing in Long-Term Stability
There’s a persistent belief that as pre-payment technology advances, post-pay will fade. That’s unlikely.
The U.S. healthcare payment system remains constrained by prompt-pay requirements, layered regulation, evolving benefit design, and complex administrative infrastructure. Errors are an inevitable byproduct of that complexity.
The advantage does not lie in eliminating every overpayment before it occurs. It lies in learning from the ones that do.
Claims will continue to be paid within 30 days – and even faster.
The organizations that build durable financial stability are the ones willing to spend more time understanding why certain claims were paid incorrectly, and ensuring they’re not paid incorrectly again.
That’s not backward-looking.
It is how payment accuracy becomes predictable.
About the Author
Steve Palma is a healthcare executive who focuses on turning complex payment systems into clearer, more reliable financial outcomes for health plans. He is the President and General Manager of Penstock, where he leads a human-led, technology-enabled approach to post-payment auditing that uncovers root causes of claim inaccuracy and strengthens long-term performance.
Throughout his more than 25-year career in healthcare, Steve has worked across plan operations, payment integrity, and growth-stage organizations to build programs that don’t just recover dollars, but improve the systems behind them. He has held leadership roles at WayMark Associates, EmblemHealth, Cotiviti, and Oxford Health Plans, and is a consistent advocate for using post-pay insight to improve pre-pay precision and financial predictability.
