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The 21st Century Cures Act, a major piece of federal health legislation passed in 2016, included provisions to address a widespread problem associated with electronic health records (EHRs): patient matching. Lacking a universal system for this, health care providers often have trouble linking patients to their records at the places where they have obtained care.

The new law: Requires the Government Accountability Office to study the approaches that hospitals and providers currently employ for patient matching, and ways to improve the matching rates.

Establishes a Health IT Advisory Committee, which will propose a policy framework for interoperability, including how to accurately locate the right patient file and avoid duplicate records.

Despite these steps, more work is needed to deliver on the promise of EHRs.

Ideally, a patient’s health data from a doctor’s office in Des Moines, Iowa, should be accessible to a hospital in New York City. Yet patient records often can’t be found —even within a single health system—or end up matched to the wrong person. There is a host of reasons for this. For example, patients may have the same or very similar names; typos or missing information can prevent accurate matches; and various EHR systems use formats that do not allow for easy data sharing among them.

As a result, duplicate records are created or patients are matched to the wrong health record. Such problems can endanger patients, result in duplicative medical tests, delay treatment, and significantly increase medical and administrative costs. Research has shown that as many as 1 in 5 patients within a health care system is not accurately matched to the appropriate record. And one report found that as many as half may not be matched when records are transferred from one facility to another—for instance, from a specialist’s office to a nursing home.

While the 21st Century Cures Act will help efforts to understand and mitigate patient matching problems, real progress will require private and nonprofit health care systems, EHR vendors, and patient advocates to come together to develop a single, national solution.

Pew is researching policies and private sector actions that could improve patient matching rates, including: Examining how specific data fields and formatting can affect matching, such as whether standardizing birthdates or addresses yields significant improvements.

Researching patient perspectives on the use of unique identifiers such as biometrics—for example, a palm or retinal scan—as a tool to improve matching rates.

Evaluating other approaches to patient matching and whether they can be effective on a national scale.

Ben Moscovitch is a manager with The Pew Charitable Trusts’ health information technology program.