The challenges associated with patient matching can’t be solved by technology alone. At a more basic level, better quality data and information culled from outside sources is a critical initial step toward innovation.
Obtaining that data is necessary to test new technology or systems that can improve patient identification, according to the Journal of the American Health Information Management Association (AHIMA).
“Organization and healthcare professionals are understandably cautious in applying innovation to this long-standing problem, as the consequences of mismatching records can be profound,” the authors wrote. “But this caution is not a reason to do nothing and wait for a silver bullet that some believe will come with a national healthcare identifier.”
Patient identification errors are listed among the top 10 patient safety dangers in 2017, according to the ECRI Institute, which has previously identified the potentially fatal consequence of wrong-patient errors. Patient matching has become a focal point for lawmakers and advocacy groups that see it as a growing concern as EHRs become more ingrained throughout the industry.
While innovations like neural networks appear to be a promising automated solution to matching patient data, the Journal of AHIMA highlights the importance of tapping into external data sources from credit bureaus or loan servicing organizations. Michael Skvarenina, CIO at Holy Name Medical Center in New Jersey, told the journal that most healthcare providers already work with credit bureaus in some capacity. Those partnerships are often simple to expand to meet the demand of matching patient data with up-to-date sources.