The patient matching problem and ideas on how to solve it

It seems obvious that for physicians to deliver the best care they should have accurate records on each patient’s medical history, including diagnoses, lab results, imaging, medications, surgeries, etc.

But linking electronic patient medical records across institutions and time – called interoperability – requires something that no one seems to have figured out how to do on a large scale: patient matching

Patient matching means knowing with certainty that a piece of medical information belongs to the correct person. It’s no small feat to accomplish patient matching, what with disparate electronic health record systems, transitions from paper records of past and patients moving around between various and unrelated medical groups and hospitals.

On Oct. 2, the Pew Charitable Trusts released a 50-page report with recommendations on how to solve the patient matching conundrum. Pew also held an archived panel discussion on the issue.

Pew came up with some interesting ideas on how to improve patient matching after meeting with patients, providers and others on the topic.

They delved into four ways to potentially improve patient matching: unique patient identifiers; patient-empowered solutions; demographic data standards; and referential matching (data collected outside health care, such as from credit bureaus, to bolster patient identity). Long-term strategies recommended included:

  • Entrusting a single organization to oversee a nationwide patient-matching strategy;
  • Launching pilot projects for patients to use their smartphones to help match records;
  • Setting standards and infrastructure for using biometrics for secure matching by creating unique patient identifiers.

As many as one out of five patients may not be matched to all the right records held at their provider, according to one estimate cited in the report. Match rates between health organizations is even lower, as low as 50 percent, according to another figure cited in the report, even among providers who share the same electronic health record vendor.

Patient matching errors are bad for patients and providers. As one example, care for an 11-month old twin was documented in her sister’s record instead of her own, resulting in the failure of a health system to recoup $43,000 in medical costs from an insurer, according to the Pew report.

The Pew report is helpful for journalists seeking to learn the reasons behind the barriers to patient matching, and how health systems today are approaching the problem. There’s a handy chart on the typical life cycle of a patient match.

The report is instructive especially since Congress is taking an interest in patient matching. The 21st Century Cures Act requires the Government Accountability Office to produce findings on what steps are being taken to reduce patient matching errors. The 2016 law also requires the Office of the National Coordinator for Health IT (ONC) to develop an interoperability policy, which includes accurate patient matching.

Further reading:

Enhanced patient matching critical to achieving full promise of digital health, Pew

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