Another option is to consider a centralized registration and/
or scheduling model to reduce variation in how staff collect and
enter data. Registration scripts may also be helpful. Children’s
Minnesota developed these scripts when it initially imple-
mented an EHR in the early 90s. “Over time, departments had
morphed these documents into their own materials,” says Nor-
een. “Now, we’re taking a step back and saying, ‘OK, everyone
needs to capture the same information.’”
Departments using a “quick registration” (i.e., only asking for
patient name, date of birth, and city/state) may also need to re-
consider their workflows so that staff capture and/or validate
complete demographic information, says Chaundy, adding that
contracted labs should be at the top of the list.
3. Collect the right type of data. Children’s Minnesota no
longer collects the Social Security Number (SSN). Noreen says
it’s because patients sometimes don’t know their own SSN—
prompting staff to enter a dummy number to bypass that portion of the registration—or staff accidentally transpose numbers
or enter the wrong numbers, compromising data integrity.
Many organizations are moving away from the SSN to prevent
medical identity theft, says Chaundy. “Cell phone numbers are
really starting to be a great identifier,” she adds. “You know nobody wants to change their cell phone number.” Email address
may also be helpful in terms of matching patients, she adds.
In some cases, organizations may need to look beyond basic
demographic data. Children’s Minnesota can’t necessarily rely
on phone number or address because these identifiers are not
unique to each patient. That’s because the address and phone
numbers of the patient are those of their parents and are often the
same for siblings. Even patient name can be tricky when there are
multiples because parents sometimes name their children a vari-
ation of the same name (e.g., twins named Jaime and Jayme). To
match patients with more confidence, Children’s Minnesota has
started to collect information such as birth order, birthplace (city
and state), mother’s maiden name, and multiple birth indicator.
4. Educate registration personnel. “This is probably the best
thing organizations can do,” says Grannis. “If you can start with
high-quality data at the point of registration, you have gone a
long way in terms of dramatically improving your data quality
and, subsequently, your matching process.”
Organizations may also want to consider requiring registration staff to meet a quality threshold and provide additional
training if they don’t meet it, says Chaundy.
Education should also include individuals who perform the
registration function as a secondary job responsibility. At Kansas
Heart Hospital in Wichita, Kansas, for instance, unit clerks (not
HIM staff) register patients between 6:00 p.m. and 6:00 a.m. It’s
important to ensure that these individuals understand the downstream effects of the data they capture, says Stephanie Costello,
MS, RHIA, coding and reimbursement specialist at Kansas Heart
5. Engage patients. Ask patients to validate demographic information on the computer screen or input information using a key-pad to avoid errors and omissions, says Grannis. Enabling patients
to complete mobile intakes in advance can also reduce errors.
How HIEs Can Help
Fortunately, the burden of patient identity management doesn’t
lie solely with healthcare organizations. Experts say HIEs themselves can also improve identity management in a variety of ways.
For example, many HIEs differentiate between authoritative and nonauthoritative sources, depending on the quality
and completeness of a participating provider’s admission, discharge, and transfer data, says Grannis. Authoritative sources
can create and update identities while nonauthoritative sources
can only link to existing identities. This distinction helps maintain data integrity throughout the HIE, he adds.
KeyHIE employs a group of individuals whose sole responsi-
bility is to help organizations improve and validate their data,
says Chaundy. “We view ourselves as an extended member of
the team at each organization to make sure we’re constantly
scrubbing the data.”
HIEs can—and should—educate providers, says Thompson.
“HIEs are leaders in patient matching, They’re very skilled at this
and can offer insights into best practices and lessons learned.”
Jaime Bland, CEO of the Nebraska Health Information Initiative (NEHII), agrees, adding that all HIEs must look beyond data
query and retrieval to focus on data quality and provider education. “We see all kinds of challenges with using different EHRs
and different EMPI solutions,” she says. “The more diverse your
data sources, the more challenges there are from a comprehensiveness perspective. HIEs are uniquely positioned to inform
providers about this.”
Close Doesn’t Count: Patient
Matching Challenges in HIEs