Reps Kelly Foster: MATCH IT Act Patient Matching Legislation Reintroduced

• Reps. Mike Kelly (R-PA) and Bill Foster (D-IL) reintroduced the MATCH IT Act in March 2025 to address patient matching errors.
• The bill, also known as the Patient Matching and Transparency in Certified Health IT Act, aims to improve US healthcare patient data accuracy.
• Inaccurate patient matching accounts for one-third of healthcare claim denials, costing the average hospital $2.5 million annually.
• The healthcare industry loses an estimated $6.7 billion each year due to these errors, with match rates sometimes as low as 50% between organizations.
• The MATCH IT Act has backing from AHIMA, HIMSS, CHIME, AMIA, and the American College of Physicians, though some suggest hybrid strategies might be more effective.

The healthcare industry loses an estimated $6.7 billion each year due to these errors, with match rates sometimes as low as 50% between organizations.

In March 2025, a significant legislative effort aimed at improving patient data integrity in the United States healthcare system was reintroduced. Representatives Mike Kelly (R-PA) and Bill Foster (D-IL) brought forward the MATCH IT Act, formally known as the Patient Matching and Transparency in Certified Health IT Act, to address the persistent and costly problem of patient matching errors.

This bipartisan bill seeks to tackle a widespread issue that has long plagued the US healthcare patient data accuracy landscape. Its reintroduction signals continued congressional attention to the challenges of reliable patient identification across diverse health information technology systems, a critical component for effective healthcare delivery and administration.

The need for robust patient matching legislation is underscored by the severe financial and operational impact of current inaccuracies. According to research from Black Book Research, a staggering one-third of all healthcare claim denials can be directly attributed to errors in patient matching. This issue translates into substantial financial losses for healthcare providers.

On average, a single hospital incurs an annual cost of $2.5 million due to these patient matching inaccuracies. Expanding this to an industry-wide scale, the U.S. healthcare sector faces an estimated $6.7 billion in losses each year because of these data discrepancies. Furthermore, past reports from Pew Charitable Trusts have highlighted the severity of the problem, indicating that patient match rates between different healthcare organizations have been observed to be as low as 50% in certain interoperability scenarios, emphasizing the difficulty in achieving consistent interoperability patient identification.

The reintroduction of the Reps Kelly Foster MATCH IT Act has garnered support from several prominent healthcare industry organizations. Groups such as AHIMA, HIMSS, CHIME, AMIA, and the American College of Physicians have publicly backed the Patient Matching and Transparency in Certified Health IT Act, signaling a broad consensus on the urgency of addressing patient matching challenges.

Despite this widespread support for the MATCH IT Act patient matching legislation, some analyses suggest that the bill, in its current form, may not fully resolve the fundamental issues contributing to patient matching inaccuracies. These perspectives often advocate for alternative approaches, such as the implementation of hybrid deterministic-probabilistic strategies, as potentially more effective pathways to achieving comprehensive and reliable patient identification.

The ongoing struggle with accurate patient matching has profound implications for the entire healthcare ecosystem. The direct link between poor patient identification and healthcare claim denials patient matching creates significant financial burdens for providers, impacting their operational stability and ability to invest in patient care. The estimated billions lost annually underscore a systemic inefficiency that demands a robust solution.

Ultimately, the push for improved US healthcare patient data accuracy, exemplified by legislative efforts like the MATCH IT Act, is crucial for fostering a more efficient and financially sound healthcare system. Enhancing interoperability patient identification is not merely an administrative goal but a foundational requirement for reducing costs, streamlining processes, and ensuring the integrity of patient records across all healthcare touchpoints.

Healthcare lawyers and compliance officers should monitor legislative efforts like the MATCH IT Act, as the persistent problem of patient matching errors and associated financial losses (e.g., claim denials) signals a growing regulatory focus on data accuracy and interoperability standards, which could lead to new compliance obligations or increased scrutiny for healthcare providers.

Source: Original reporting via industry analysis