Containing health care costs: Analytics paves the way to payment integrity
Health care organizations look to data-driven analytics to target payment integrity issues
By Ben Wright, Senior Solutions Architect, Security Intelligence Practice, SAS
In an effort to contain costs, health care organizations (HCO) are changing the way they pursue claims overpayments. Traditionally, the focus was mainly on fraud. But today – in a process more broadly labeled payment integrity – plans are seeking to uncover a wider range of abuse, waste and errors in claims processing. And data-driven analytics is making that possible.
The past
Historically, HCOs had few tools for uncovering fraud and most of them did not involve analytics. Along with tips from law enforcement, outlier models and business rules, HCOs relied heavily on claims adjusters to spot anything suspicious. But keeping adjusters up to date on the latest fraud schemes requires ongoing training.
In the US alone, payment integrity issues point to a staggering $800 billion in health care losses each year.
Also, in order for a claim to qualify as fraudulent, you must prove in court that an intent to deceive for the purpose of financial gain existed. Less than 10 percent of the money lost to fraud was ever recovered this way. What’s more, fraud accounts for only a fraction of the total loss due to billing errors. According to Stonegate Advisors, in the US alone, payment integrity issues point to a staggering $800 billion in health care losses each year.
That’s why many HCOs are moving away from the pay-and-chase model. Now, they are looking beyond the claims department and taking an enterprisewide approach to spotting errors, abuse and waste throughout the entire claims process. The goal is to spot fraud and billing issues earlier in the cycle and stop losses before they occur.
The present
Payment integrity covers a broad spectrum of behavior from organized crime to simple mistakes in filling out a form to eligibility fraud. It also covers subrogation, where another company is responsible for a piece of the claim – for instance, an auto accident where liability should be split between the medical insurer and the auto carrier.
A key enabler in payment integrity is data-driven analysis. Analytics can quickly search though unstructured textual data in claims. It can mine through electronic medical records, call center logs and information from provider offices. Analytics can also analyze third-party data and point to possible collusion – for example, a doctor’s office making large purchases from a medical supply store it also owns.
Analytics can provide insight into complex schemes that are difficult or impossible to understand with traditional techniques. Analytics also builds consistency and creates a common platform for decision-making between various departments within an organization. In other words, analytics gives you a single version of the truth.
The future
Why is payment integrity so important? Because it plays a key role in helping HCOs contain their costs. Since the Affordable Care Act (ACA) passed in the US in 2012, insurers have had to price plans in a way that keeps customers happy yet still produces a profit, albeit a thin profit.
The ACA includes a number of strict regulations that put tremendous pressure on HCOs to reduce costs. For example, the act requires insurers to pay out that 80 to 85 percent of premiums on claims. That leaves only 15 to 20 percent left for administration and profit.
Many insurers are merging in an effort to gain the benefits of size and scale to help manage costs. At the same time, HCOs are competing on public exchanges. The ones that survive in the new world will be those that can trim waste to offer the most competitive rates. Advanced analytics is helping provide answers.
How much are fraud, error, waste and abuse costing your organization? Costs to insurers are huge – as much as 25 percent of payments made. But data management and analytics can save the day. The white paper, Health Care Payment Integrity through Advanced Analytics, discusses how data can be used to predict and detect loss in all its forms.
As a Senior Solutions Architect, Ben provides support in planning, marketing and implementation of healthcare fraud detection, investigation management and payment integrity solutions for state governments and commercial healthcare. He previously worked in pre-payment fraud detection, data analytics and payment integrity process support for more than 20 years. Ben holds a BA from Dartmouth College, has been a frequent presenter at NHCAA, and holds an active AHFI certification.
