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Info-blocking rule gives nod to patient-matching improvement
n The ONC in its final rule released
n Long-awaited rules
following five data
in March added new types of
on interoperability and
information-blocking
demographics to the U.S. Core Data
elements to the USCDI’s
for Interoperability, a standardized
patient demographics
from CMS and the Office
data class:
set of data elements developed by
of the National Coordinator
1. Current address
the agency. That additional data can
for Health Information
Technology pointed to
be “useful to provide better care
2. Previous address
patient matching as a reason
and assist with patient matching,”
3. Phone number
according to the rule; however, it’s not
4. Phone number type
to expand demographic data
required that the information be used
collected from patients.
5. Email address
for matching. n The ONC added the
mented a system that identifies patients based on the pattern matches between different facilities is more challenging.
of veins in their hands; it has been a mainstay of the system’s In focus groups conducted by Pew, biometrics proved
patient-matching strategy since 2011. Patients who come to be one of the most popular matching solutions patients
visit a hospital or clinic place their hand on a device—“give cited interest in. But without the entire healthcare system
us a low-five,” Wingo says—that scans their palm. adopting a single, standardized form of biometrics, it won’t
That scan, along with a patient’s date of birth, are the two be useful for matching between facilities.
data elements used to identify patients. University of Utah Health gets daily reports from a state-
Harris Health’s duplicate record rate is now 7%, down wide health information exchange, UHIN. The reports in-
from 10% before installing the palm-vein scanners. And clude information on which of the system’s primary-care
because of more accurate matching, the system now em- patients visited an emergency department and were ad-
ploys just one full-time staffer to evaluate and merge possi- mitted to or discharged from another organization.
ble duplicate records, instead of a full team. The process to match patient information from other or-
The vast majority of patients have enrolled in the ganizations is set up in the back end, so it doesn’t require
palm-scanning system, according to Wingo. There was manual intervention from the care management team at
apprehension among some patients at the beginning, sys- University of Utah Health, said Shelly Medley, care man-
tem leaders acknowledged. Much of the concern related to agement supervisor at the system.
whether the biometric information would be UHIN’s reports typically include a patient’s
shared with law enforcement. The palm-vein medical record number, some demographic
data is only used internally and not shared out- Inaccurate patient data, the hospital they went to, and their ad-
side the organization, Serna said. accounts for roughly mission and discharge date. Armed with that
identification
information, University of Utah Health’s care
To make sure patients understood that, Har-
its hospitals and clinics in a phased approach. $1,950 management team can reach out to patients
ris Health rolled out the palm-vein scanners to
to see if they need a follow-up appointment,
For each of the facilities in which the technol- as well as to ensure they understand any care
ogy was live, staff hung posters in English and in duplicative plans or new medications.
Spanish explaining the new process and would medical-care costs Medley said the care management team will
direct patients with additional questions to pa- per inpatient and always look up the patient by their medical re-
tient advocates. $1.5 cord number—provided in UHIN’s reports—to
double-check it’s the correct patient, but there
Leaving the system million are rarely any problems.
But matching records to palm scans doesn’t in denied claims University of Utah Health has been work-
work for everything. Harris Health still relies on per hospital ing with UHIN for years. That has included a
searching for patients based on their standard each year patient-matching improvement project that
demographic data elements, like names and UHIN, University of Utah Health and Inter-
dates of birth, when matching patients with their records mountain Healthcare collaborated on from 2015 to 2017,
from outside the health system—including from a local which involved developing protocols for Utah’s poison-con-
health information exchange. trol center to collect demographic information from callers.
While programs that recognize patients based on palm, “The key to any HIE is matching patients across different
fingerprint and iris scans have proved useful for match- systems and different organizations,” said Cody Johansen,
ing patients within the same organization, getting good UHIN’s director of operations.
18 Modern Healthcare | June 8, 2020