Balancing Privacy and Efficiency: Should Medicaid Use Sensitive Data to Reduce Improper Payments?

Note [M.B.]: We’re experimenting with our posts' format, schedule, and content at OpenHealthPolicy. Make sure to read to the end of today’s post, where you can respond to a poll about the policy question underlying today’s post. We look forward to seeing what you readers think about this issue.

Medicaid is one of the black holes that comprise the unsustainable fiscal outlook in the U.S. While most people want to reduce government waste, improper payments are an area that’s arguably not receiving sufficient attention. In 2022, Medicaid programs made around $80 billion in improper payments, an incredible figure—almost twice Medicaid's spending on prescription drugs ($44 billion), and thus potentially an area where reform could save taxpayers without harming those in need.

Understanding Improper Payments: Case Studies of Fraud and Administrative Errors

Improper payments are payments that do not meet CMS program requirements. These include fraudulent billing, administrative errors, insufficient documentation, and other similar sources. The Government Accountability Office has repeatedly identified Medicaid as a high-risk area due to its susceptibility to improper payments, emphasizing the need for systemic improvements to ensure fiscal responsibility​. Let’s look briefly at some examples:

The U.S. Attorney's Office, Western District of Virginia, recently fined Health Connect America $4.6 million for billing Virginia Medicaid for services not provided. In another case, a doctor who owned medical practices in Maryland and Delaware was fined $3 million and had to surrender his medical license because he improperly billed Medicaid programs. However, these are just a few instances. According to a Reuters investigation, "more than one in five of the thousands of doctors and other healthcare providers in the U.S. prohibited from billing Medicare are still able to bill state Medicaid programs." Additionally, the District of Columbia paid $79 million to 269 of the 1,800 providers after their terminations elsewhere.

Such cases naturally paint a grim picture, but the data shows that while fraud receives a lot of attention, the majority of improper payments are simply payments where there’s insufficient information to determine whether the recipient was eligible.

Source: Supplemental data, 2022 Payment Error Rate Measurement (PERM) Report

Balancing Privacy and Efficiency

One policy solution is for CMS and state Medicaid programs to make better use of (often) sensitive data to determine program eligibility. By using our rapidly growing capabilities in AI and analytics, technology could be used to verify eligibility and service provision, potentially even in real-time, and thus prevent improper payments before they occur.

So, the question becomes, are we willing to trade off some privacy in order to improve eligibility determinations and thus reduce the rate of improper payments? We are curious to see what you, our loyal readers of OpenHealthPolicy, think about this question. Should CMS and state Medicaid programs be equipped to better use (often) sensitive individual data to reduce improper payments? Let us know what you think by answering the poll and in the comment section if you are so inclined.

For more posts related to this topic, see our previous posts:

The Sexy and Not-So-Sexy Future of AI in Healthcare - Markus Bjoerkheim, Matt Mittelstadt, and Sam Alburger

Precision Policy: How Big Data is Reshaping U.S. Healthcare - Ali Melad

Red ink: Congress can’t control spending without reforming how we pay for healthcare - Markus Bjoerkheim

The Misallocation of Federal Medicaid Dollars - Liam Sigaud

Medicare Spending: Physician Services Are a Much Bigger Problem than Drug Prices - Elise Amez-Droz