Study: Data standardization improves patient matching

Standardizing address information and last names could help to link patient health records by as much as 8 percent in the United States.

Such relatively simple standardization efforts could result in more than 2 billion additional records matched to patients, research suggests.

That’s the finding of a study, published in the Journal of the American Medical Informatics Association, from researchers at the Regenstrief Institute, Indiana University Richard M. Fairbanks School of Public Health at IU–Purdue University Indianapolis, IU School of Medicine and The Pew Charitable Trusts.

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Regenstrief Institute

Researchers tested patient matching accuracy using standardized addresses, full birthdates, last names, Social Security numbers and telephone numbers with four real-world datasets—health information exchange records, public health registry records, Social Security Death Master File records and newborn screening records.

What they discovered is that standardizing addresses had the greatest impact on data matching across all four use cases, while last names had a smaller effect.

“Address is a field rife for variation, so this is a great opportunity for standardization,” says Shaun Grannis, MD, lead author and director of the Regenstrief Center for Biomedical Informatics. “Standardizing data on a broader scale would ensure that patients and clinicians have better data on which to make decisions, which would enhance both the quality of care and patient safety.”

“This first-of-its-kind research shows that setting standards for demographic data—addresses in particular—could put a significant dent in healthcare’s perennial problem with correctly matching records for the same patient,” says Ben Moscovitch, project director of the health IT initiative at The Pew Charitable Trusts. “Now it’s time for the federal government to require the standardization of data that help link an individual’s medical records—which is a key step to fully realizing the safer, well-coordinated care that electronic health records promise.”

Patients are often matched to their medical records through demographic information, such as name, date of birth or sex. However, a recent Government Accountability Office audit found that “inaccurate, incomplete or inconsistently formatted demographic information in patients’ records” is posing challenges to matching medical records.

Also See: Patient matching hampered by demographic data

Particularly problematic is the matching of medical records for newborns and multiple-birth siblings such as twins, according to the report.

Specifically, auditors noted that EHRs “don’t always contain correct information (for example, a patient may provide a nickname rather than a legal name) and that health information technology systems and providers use different formats for key information such as names that contain hyphens.”

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