Healthix, a large health information exchange vendor serving New York City and Long Island, is going live with a new service to improve the matching of patients with their records.

The HIE, with a database of 16 million unique patients, matches patient records using information from multiple sources and serves about 1,400 provider facilities throughout the region.

Healthix in August delivered 430,666 clinical event notifications delivered to providers along with 155,035 clinical summaries delivered to electronic health record systems via CCD or C-CDA continuity of care documents, and about 8,000 secure messages are sent monthly, says Tom Check, president and CEO. The company also offers analytics services to predict patients at risk and needing interventional care.

Healthix uses a master data management system from IBM which works well for routine matching purposes, such as a patient who checks in as Peggy for one appointment, and as Margaret for another appointment, Check says. But the system often can’t match more complex records with certainty to decide if disparate records match to a unique individual, Check says.

Also See: 7 tips to improve patient identity processes

So an outside firm was hired to manually match more troublesome records. But Check wanted an automated matching system to avoid transferring files outside the organization, preferring to keep data within the HIE for security purposes.

That started a vendor search that lead to proof-of-concept trials with three companies. Healthix took 8,000 patients with near matches from the IBM database, representing about 30,000 records, and compared the companies’ capabilities. One vendor, Verato, was able to reduce the number of different records by 42 percent immediately, Check says. Verato then confirmed veracity of the matches without the combining of records that should not be combined, Check says. He also liked being able to just send one patient file for verification in real time.

Healthix conducted the trials with actual records and tried to resolve issues with each of the companies. “That’s important; this is not just a theoretical exercise, but making it work in the real world,” Check says. “Doing a real trial means a lot. It’s hard work, but you learn a lot.”

Other HIEs should take a look at the level of patient-matching capability they have and seek options for an automated solution, Check advises. “All HIEs face this need. We all have software that can resolve identities based on data we have. But we don’t have changes in patient demographics between visits.”

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