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 Missing demographic data, outdated mailing addresses, and telephone numbers have made it very difficult to accurately deliver and track test results.
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 organization.
“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.