The volume of healthcare data is expanding at an unprecedented rate, and nowhere is this more evident than in the pharmacy sector. As prescriptions, claims, and regulatory requirements evolve, the influx of data presents both an opportunity and a challenge—especially when it comes to fraud, waste, and abuse (FWA) detection.
While advancements in technology enable better data analysis and improved healthcare outcomes, they also open new doors for bad actors seeking to exploit system vulnerabilities. The complexity of pharmacy claims, coupled with gaps in Medicare communication and rapidly evolving AI-driven fraud schemes, makes it critical for healthcare payers to stay ahead. Without the right tools, identifying FWA can feel like finding a needle in a haystack.
In this blog, we explore how pharmacy data has grown in volume and complexity, highlight the emerging risks within Medicare and prescription intelligence, and demonstrate how Codoxo’s AI-driven Suspicious Trends detector helps plans efficiently analyze claims to pinpoint fraud with confidence.
Technological and data advancements
Technology is advancing at an unprecedented pace, with innovations emerging more rapidly and frequently than ever before. According to Data Bridge, the U.S. tech industry is expected to see a compounded annual growth rate (CAGR) of 8.4% over the next 5 years reaching $669 billion by 2031. Furthermore, cloud computing is expected to see a CAGR of more than 20% in the same period. The same report also noted that 90% of Americans have access to the internet.
Significant growth
One compelling reason rapid growth matters is the sheer volumse of data, with 90% of the world’s data being created in just four years between 2019 and 2023. Data Bridge Research also shows that the world’s data will double every year going forward. Luckily the cost to store data has dropped exponentially over the last 20 years. In 1990, the cost to store 1GB of data was $9,000, today that same 1GB of data can be stored for a few pennies. While data provides us with an infinite number of ways to analyze, describe, and infer, we must be ready to accept, and process said data in a manner that is best for our organization(s). We must also be prepared to detect those who are using this ever-growing technology for nefarious purposes, such as Fraud, Waste, & Abuse (FWA) in the medical field.
According to Data Bridge, machine learning is expected to grow by 38.6% (CAGR). This expected growth includes an estimated 8.4 billion “voice assistants,” – devices you’ve likely interacted with, such as when reaching out to customer support at your bank. Again, the issue we face is how this technology is being used. During the NHCAA conference, a case study discussed the use of machine learning voice assistants to contact Medicare patients to get them to provide their personal health information that was later used to steal their identities and commit fraud. A similar case study showed how AI generated medical records were used to fraud many payors into paying for claims that were not legitimate.
Medicare and prescription intelligence
To start, it’s important to understand recent Medicare reforms. According to CMS there were six “key” reforms passed in 2022 due to the Inflation Reduction Act. One of these reforms involves a restructuring of Medicare Part C, which will now be referred to as Medicare Advantage. This program serves as an “all-in-one” alternative to Original Medicare, combining various coverage options into a single plan. These benefits can include dental coverage, vision, over-the-counter items, and more. Changes to Part B are even more concerning from a FWA viewpoint. Benefits included with Part B include covering PrEP drugs at no cost to the patient along with 8 counseling visits, 8 HIV tests, and 1 screening for Hep B. Furthermore, it was noted that, currently, Part B and Part D do not communicate with each other. This means that a claim may be paid by Part B and again by Part D.
How can Codoxo assist your plan with identifying potential prescription issues?
While there are many ways for the Codoxo platform to identify and flag these claims for review, one detector, Suspicious Trends, has proven to be one of the most beneficial. In short, Suspicious Trends detects irregular and potentially fraudulent patterns within insurance claims and provider behavior, enabling proactive intervention to safeguard against fraudulent activities and protect the integrity of insurance programs. Codoxo’s pharmacy team has seen, and continues to see, great success in using this detector to identify fraudulent claims. The lack of communication between Medicare plans does not hinder the detection of claims through Suspicious Trends. On the contrary, this detector was specifically designed to identify such patterns.
If you are a pharmacy claims expert, you may still be questioning how to narrow down potential FWA using this detector. As an expert you know that there are many data points or attributes of a pharmacy claim that can be used for analysis, and sometimes it’s the simple things that point us in the direction of FWA. For example, when reviewing the flagged providers for the Suspicious Trends detector we are provided with a few attributes including provider peer group, total paid exposure, number of claims, line count, patient count, line of business count, and some more information regarding the detector sub-category (when applicable).
When reviewing this data there are a few things to look at to help you determine if the provider requires further investigation.
- Total Paid Exposure vs. Number of Claims
- A higher total paid exposure with fewer claims can be a red flag (cost per claim)
- Total Paid Exposure vs. Patient Count
- A higher total paid exposure with fewer patients can be a red flag (cost per patient)
- Line of Business Count (LOB Count)
- A higher total paid exposure across 3 lines of business is less of a concern than a higher exposure within only 1 line of business
- Number of Claims vs. Patient Count
- A high number of claims with a lower patient count can be a red flag (claims per patient)
As you can see, the first set of data you encounter when reviewing providers flagged for Suspicious Trends provides you with quick insight to make an informed decision as to whether a provider should be investigated further. The further you explore the Codoxo platform the more information you will be provided with, which means the comparisons above will become clearer and allow you to investigate at the claim level as opposed to solely at the provider level. Pharmacy experts will begin to see trends between each claim line validating your suspicions and the claims flagged by Codoxo’s Suspicious Trends detector.
https://www.panfoundation.org/everything-you-need-to-know-about-medicare-reforms/