In healthcare payment integrity, provider audits are about as welcome as a surprise visit from your conspiracy-theory-loving uncle—time-consuming, occasionally abrasive, and usually filled with pseudo-logic. But audits, like your uncle, aren’t inherently bad, they’re just often misguided.
Traditionally, payers have cast wide nets, reeled in countless irrelevant claims, and asked providers to navigate bureaucratic hurdles over minor clerical oversights only to claw back money after the payment has been made. Thankfully, we now have a smarter partner: Artificial Intelligence (AI).
1. Precision Selection: No More Needle-in-a-Haystack Audits
Historically, audits resembled searching for your keys by emptying every drawer in your house. Sure, you’ll eventually find them, but you’ll also waste hours sorting through irrelevant clutter. Auditors would comb through claims, randomly checking stacks of data, looking—maybe even hoping—for a red flag.
AI flips this model, targeting only claims with significant risk factors—those truly worth scrutiny.
For instance, a predictive AI model can instantly flag irregular billing patterns, such as an orthopedic surgeon billing for 32 hours of Evaluation and Management (E/M) codes in the same day. Unless they’ve invented a time machine, providers can’t jam 32 hours of work into a 24 hour period.
By focusing only on these targeted claims, providers are spared needless audits for routine, accurate submissions.
2. Speedy Evaluations: Goodbye Snail Mail, Hello Instant Gratification
For providers, in traditional processes, waiting for a claim payout can feel like waiting for a rideshare at an airport. You’re watching your Uber driver circle the airport over and over, constantly taking wrong turns—all you want to do is get home. It’s frustrating, slow, and unnecessarily anxiety-provoking. Much like the guessing game of knowing when your driver will actually arrive (two minutes becomes four, four becomes six), there’s a guessing game on whether or not providers will even receive payments and, if so, when.
AI accelerates evaluations from days or weeks down to mere minutes or hours. For example, complex DRG claims, historically taking days to process and review, can now be evaluated swiftly by AI, drastically reducing waiting times and improving cash flow for providers. Not only does this benefit the provider, but the payer and patient as well. For the payer, there’s a reduction in provider abrasion, strengthening the relationship between the payer and provider. With less time spent focused on admin, providers can focus on patient care rather than worrying about delayed reimbursements.
3. Consistency & Objectivity: Eliminating the Mood-of-the-Day Effect
Imagine two identical sepsis cases submitted separately: one reviewed by a medical director before breakfast, and the other by a different medical director, right after lunch. The human brain can produce very different assessments depending on everything from blood sugar levels to whatever podcast is blaring. Sounds absurd, yet human psychology is really that fickle. We are inherently pattern-loving creatures, susceptible to recency bias—the tendency to allow recent experiences to disproportionately influence decisions. So, if the last claim an auditor reviewed was problematic, the next claim may be unfairly scrutinized, even subconsciously.
AI doesn’t carry these biases or emotional baggage—unless explicitly programmed to mimic our flaws. AI serves as a consistently objective arbitrator of healthcare policies and clinical guidelines, applying standardized criteria to every claim every time.
4. Succinct and Actionable Feedback: Helping Providers Correct and Prevent Mistakes
Traditional audit feedback can often feel like having your palm read—vague, ambiguous, subjective, and not particularly helpful. AI-driven evaluations, by contrast, offer clear, concise, and actionable feedback. They precisely highlight how discrepancies match up to policies, giving providers a straightforward path to resolution before a denial or payment is issued.
For instance, AI feedback might specify that a diagnostic code was used incorrectly, along with guidance on the correct usage, allowing providers to swiftly resubmit rather than navigating through prolonged dispute processes.
Collaboration Amplifies AI Benefits
AI isn’t magic—but it gets pretty close when payers and providers collaborate. Shared understanding, transparency, and mutual trust enhance the capabilities of AI-driven payment integrity solutions. Ultimately, our collective goal is deceptively simple: pay claims correctly and promptly to benefit providers, payers, and patients alike
So why hold onto antiquated practices? If AI can help us move past inherent human biases, pattern-driven misjudgments, and slow decision-making processes, isn’t it time we embrace our technological partners—at least for healthcare payment integrity?
It’s time for healthcare to swap abrasive audits for smart savings. Let AI handle the paperwork, while providers get back to the human business of patient care.
To learn more about how Machinify can assist your health plan through all steps of the payment integrity process, contact us.
