Dive Brief:
- Accurately matching patients to their health records is difficult to measure, according to healthcare providers surveyed by the Pew Charitable Trusts. Match rates are "far below the desired level for effective data exchange," Pew, which collaborated with nonprofit services firm Massachusetts eHealth Collaborative on the report, concluded.
- The two organizations interviewed providers at 18 hospitals, doctors' offices and health IT exchanges.
- The current state of patient matching provides ample opportunity for improvement, providers said.
Dive Insight:
Matching patients to their healthcare records is a ongoing problem, with current match rates between organizations as low as 50% or 60%, according to the Office of the National Coordinator.
Mismatched records can lead to care delays, patients receiving inappropriate surgery or being prescribed the wrong medicine — along with raising costs and the administrative burden for providers.
Precise data on patient matching rates is scarce as match rates are tricky to measure. Indeed, Pew found that many companies only measure duplicate records within their systems, not how often outside records can be linked with ones providers already have in house.
Additionally, many companies couldn't pinpoint their match rates because they simply don't know the universe of the records that should be related, and therefore don't know how many records should have been linked but weren't. The situation is further complicated by that fact that healthcare organizations constantly receive patient records they haven't asked for, and are therefore unprepared to match within their system.
The problem is compounded within urban health systems. Facilities in metropolitan areas are more likely to share records because their patients get care at multiple locations than their rural counterparts.
Techniques to improve matching vary in scope, method and price, Pew found. A 2018 Pew study highlighted four promising solutions: using unique patient identifiers such as biometrics, patient verification of their records via smartphone, standardizing demographic data and enacting referential matching, which compares a record to a centralized database.
Most healthcare players use purchase software to automate matching and employ, on average, four to five employees full-time to manage mismatched records, Pew found. But some players are using more promising techniques.
Health cybersecurity firm Imprivata partnered with referential matching firm Verato early April in an attempt to tie biometric data to Verato's cloud-based master patient index and provide a comprehensive patient matching solution. And an advisory group to ONC voted earlier this week to encourage the government to adopt some sort of standardized demographic database to assist in linking records, such as U.S. Postal Service address standards.
Providers agree the industry's recent push for interoperability — the free and unfettered exchange of health information among different healthcare facilities and network — is fueling the desire for better patient matching.
HHS released two rules mid-February giving industry a push on interoperability. If they are finalized, by 2020, insurers participating in any CMS-run plans must be able to grant patients electronic access to their health data free of charge. Industry would be incentivized to adopt standardized ways of communicating with each other, and the Office of the Inspector General would fine actors found to be blocking information up to $1 million per violation.