Originally posted January 1, 2019
Here is an excerpt:
Yet nowhere can AI have a more immediate and accessible impact than in patient matching. Currently, health systems have teams of data stewards and health information management (HIM) professionals dedicated to finding, reviewing, researching, and resolving records that their EHR or EMPI has flagged as “potential duplicates.” Essentially, these employees are spending hours each day looking at, for example, a record for Jane Jones and another for Jane Smith, trying to decide if both Janes are actually the same person and if her records should be merged.
Referential matching technology can automate 50-to-75 percent of this manual effort by being an intelligent and data-driven technology. It can automatically find and resolve duplicate records that EHRs and EMPIs have missed, enabling data stewards and HIM staff to focus on higher-value projects—while simultaneously lowering the operational costs and inefficiencies plaguing health systems by automating manual work.
Ultimately, automating the discovery and resolution of duplicate records with referential matching technology can reduce claims denials to save up to $1.5 million, reduce operational costs by at least $200,000, improve the ROI of EHR deployments, and enable value-based care and patient engagement initiatives by enabling more complete and accurate patient health histories.
Health systems are increasingly making technology investments not just to reduce costs or improve efficiencies, but also because not using new technologies is becoming unethical. We have reached a tipping point where innovative new technologies are prominent, successful, and inexpensive enough for ethics to begin driving technology purchasing decisions.
The info is here.