How to approach identity matching with patients
Estimates suggest that 30 percent of healthcare identity data stored in information systems is incorrect or out of date, says J. Brent Williams, founder of Verato.
He recalls a healthcare client who had 34 different health record systems, spending millions of dollars trying to handle patient identification issues. The client tried to share data with another institution but it didn’t work because the patient, John Smith, was transgender and became Christine Jones on a specific date, but Christine’s driver’s license was not updated.
That’s just one example of why providers should stop trying to clean their data; it’s a losing battle, Williams will contend during a session at AHIMA16, Oct. 15 to 19 in Baltimore.
People remarry and their names change, and others have accents on their name that a billing system may or may not accept, says Williams, whose company sells a platform to clean, update and link customer, employee or patient records inside and across systems using commercially available identity records.
One reason providers focus on cleaning data is the need to link data across systems, adds Grace Koh, chief marketing officer at Verato. But now, technology exists to match patient identity attributes to confirm identification by assembling a longitudinal history that tracks changes over time in a patient’s name, address, Social Security number and other identifiers to ensure that a patient named Sara is documented as such, and not as Sarah.
Williams and Koh also will explain how various types of identification errors continue to occur, such as when a driver’s license is scanned but staff still don’t get the name right.
The AHIMA session, Stop Cleaning Your Data, is scheduled at 11:15 a.m. on Oct. 19 in rooms 321-323.