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Artificial Intelligence Homepage

Aidoc announces $27 million in VC funding to advance AI in imaging Brings company's total funding to $40 million

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Beyond the hype: How practical AI is enhancing radiology Insights from Imad B. Nijim, chief information officer for MEDNAX Radiology Solutions

How artificial intelligence can transform payment integrity

By Krithika Srivats

In 2013, the actress Angelina Jolie published an opinion column in the New York Times that described her decision to undergo a preventive mastectomy after testing positive for the BRCA gene, a mutation that can lead to breast cancer.

Within two weeks of the column’s publication, more than 4,500 BRCA tests were ordered across the nation, a 64 percent rise from the same time period the previous year. Interestingly, researchers found no increase in the number of breast cancer diagnoses, and mastectomy rates actually declined. This suggested that many of the tests were given to populations at low-risk of carrying the mutation. In the end, a few hundred words written by a celebrity cost the healthcare system nearly $14 million for tests that were largely unnecessary.
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Though this was a clear example of overutilization, the payment integrity programs of most health plans mounted responses that were either ineffective or non-existent. A closer look at most payment integrity programs reveal why they were ill-suited to the task.

While specific components of a payment integrity program can vary among health plans, most include a combination of human-based review and rules-based automation software to identify anomalies among thousands of claims. However, manually-driven payment integrity programs – even those augmented with automation and analytics software – identify less than half of all claims anomalies, which may or may not prove to be improper claims after further investigation. In addition, this resource-intensive and costly process was largely built on a pay-and-chase model, whereby outliers are targeted and recovery of previous paid claims are initiated.

A 2018 Gartner report, “U.S. Healthcare Payer CIOs Must Adopt Prospective Payment Integrity to Thwart Improper Claims Payment and Fraud,” concluded that health plan executives can significantly improve the financial returns from payment integrity programs” through prospective processes and “exponentially increase financial performance and improve provider relationships.”

Fortunately, technological advances have given health plans an opportunity to build a better payment integrity system – one that doesn’t just anticipate emerging trends from, say, a high-profile endorsement of an expensive medical test, but most other forms of overutilization.

The solution? Artificial intelligence (AI).

AI has been successfully applied in many areas of healthcare with proven results – from the creation of better care pathways to advances in disease research and reducing medical errors. AI also has the potential to be a significantly more reliable, efficient, and cost-effective solution to mitigate improper claims payments that cost the healthcare industry hundreds of billions of dollars every year.
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