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Jerris Heaton


Patient Matching 101: Why Getting It Right Is Critical

March 13, 2020


EHR 3 Minute Read

Patient matching is a simple concept – with increasing interoperability and availability of electronic medical records, physicians and care providers should be certain that medical information is linked to the correct patient.

However, the execution of this idea is no small feat.

With a wide variety of electronic health record (EHR) systems, the movement of patient info from physical records to these systems, and patients physically moving around, critical information can get lost in the shuffle.

Failures in patient matching can have far-reaching implications. Fortunately, there are potential ways forward.

The Problem with Inaccurate and Incomplete Patient Matching

When patient matching isn’t achieved in a satisfactory manner, a number of problems and challenges can result.

The first is perhaps the most obvious – if a patient’s information isn’t correct, how can their treatment possibly be? Incomplete and inaccurate information can lead to misdiagnosis, ineffective treatment plans, and more, all of which can have powerful negative results on patient outcomes.

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Privacy concerns also loom – patient information should remain between the specific patient and their physician, but incorrect patient matching can result in that information being disseminated to places it shouldn’t be.

Further, incorrect and incomplete patient matching wastes valuable resources. Practices can’t effectively handle the ins and out of a patient’s insurance coverage without correct information, and mistakes in patient matching lead to wasted time trying to mend them.

These obstacles have traditionally plagued efforts to improve patient matching, getting in the way of the streamlined, interoperable systems that should be the goal of the country’s healthcare providers.

Finding a Way Forward

In the fight to improve patient matching and achieve the industry’s goal of providing better patient experiences and outcomes, there have been several solutions proposed that carry the potential to move patient matching forward.

First, demographic data standards could be established at the national level, providing a clearer idea of which patient identifiers should be used in patient matching (address, phone number, email address, etc.). With more consistent standards, in theory, the odds of patients being incorrectly matched to medical data would decrease.

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Second, patients could be more empowered to verify their own information, taking a more active role in their care and helping the industry ensure they’re attached to the correct data. This solution could involve the use of mobile-device-enabled programs to offer another layer of verification.

Third, a single organization, either existing or to be created, could be tasked with overseeing a nationwide strategy for the improvement of patient matching. With a singular body managing the path forward, and potentially an NPI system assigning a new form of identification for patients, more concentrated efforts could result in real strides being made.

Finally, referential matching could also prove useful if implemented securely. By cross-referencing information collected outside the medical arena with patient data, more confirmation and better matching might be achieved.

These are only a few of the potential paths toward better patient matching, though one thing is certain – in the coming years, as interoperability and EHR adoption continue to increase, careful attention to patient matching will be necessary.



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