The COVID-19 pandemic has highlighted underlying challenges
in patient identity data matching and, in many cases, these challenges have slowed
public health efforts to respond to and contain the spread of the virus. Missing
demographic data, outdated mailing addresses, and telephone numbers have made it very difficult to accurately deliver and track
This fall, Verato conducted a survey with the eHealth
Initiative to gain a better understanding of how healthcare organizations are
using data matching and patient identity best practices in response to
COVID-19. One of the initial findings from the survey was the low percentage of organizations currently using
patient matching solutions to accurately match COVID patients to their complete
set of medical records Of the organizations surveyed, only 66% said they
were using some form of patient matching.
The survey also showed that while the challenges around
patient matching are numerous, they are especially stark for public health:
only 38% of public health organizations said they used patient matching and of
those using it, 0% had total confidence in the accuracy of the information.
Verato CEO Mark LaRow discussed this trend and cited the
complications that arise from not utilizing patient matching at a public health
“Manually matching in spreadsheets is absorbing all the
people’s time to only get it partially right. That is a real problem for the
country,” he said.
David Kates, CTO of Manifest MedEx, agreed saying that when
using manual matching, “there is no such thing as 100%, given the robustness of
the data we get and the reliance on the data entry people at the front end that
are responsible for capturing the information.”
The majority of the organizations surveyed agreed that
patient matching is a struggle that has been highlighted by the pandemic.
Mark LaRow cited the changing healthcare landscape, such as
the rise of disparate data sources like telemedicine and analytics, as one of
the reasons why the pandemic has created such a challenge for patient matching.
“It’s not just hospitals and close affiliates of hospitals
anymore, it’s public health, labs, soon it will be pharmacies as we’re
distributing vaccines. The ecosystem by which we’re exchanging patient data is
getting geometrically more difficult,” he said.
David Kates said from an HIE perspective, they have seen a
rise in interest from public health organizations that they serve in getting
accurate data for contact tracing, identifying contact information, and making caregivers
aware of positive test results.
Finally, the survey made it apparent that organizations have
minimal expectations in the short term from policy makers – about half of the
survey participants believed that the likelihood of Congress passing any sort
of patient identifier legislation in the next 5 years was very low.
William Hammond, Director at Duke Center for Health
Informatics, emphasized the need for better patient matching now, saying that
while the pandemic has highlighted the problems with patient matching, those
challenges are not new and need to be addressed.
“Until we apply technology appropriately, we will never get
to acceptable levels,” he said.
The good news is that solutions do exist, with strong
patient matching engines like Verato. According to LaRow, “If you have a good
matching engine, all that data is available to be easily and accurately
matched. Public health hasn’t paid attention to it in the past because they
haven’t had to.” he said.
Watch the recording here.