Most healthcare providers and health information exchanges agree that faulty data entry is the largest source of patient identification and matching errors in the U.S, according to a recent eHealth Initiative report.
For its State of Patient Matching in America 2019 survey, eHealth Initiative asked 118 leaders at provider and HIE organizations about patient matching efforts across the country. The eHealth Initiative was commissioned by NextGate for the report.
When asked which factors contributed to duplicate medical records entries, participants said:
· Data entry errors: 66 percent.
· Record matching/patient search terminology and/or algorithms: 46 percent.
· Poor system integration/interoperability: 42 percent.
· Registration staff turnover: 35 percent.
· Lack of industry-wide data standards: 35 percent.
When asked which innovations they thought would be most likely to impact patient match efforts, based on a one- to eight-point scale, participants said:
· Demographic data standardization: 5.7.
· Biometrics: 5.5.
· Reference of third-party data: 4.9.
· Machine learning: 4.8.