Electronic health records can allow providers the ability to exchange individuals’ health data with their colleagues elsewhere, who can then have the information they need to make the correct medical decisions about the same patient. However, patients may not always be accurately matched to their records—a problem that can occur up to half the time when individuals seek care in multiple places.
At a minimum, this can cause delays in care as providers search for a patient’s information, and hamper treatment when one person’s data are scattered across different records. At worst, a person can be matched with a record belonging to someone with similar information—name, birthdate, and so on—but a different medical history. If not caught early, that error can lead to patients receiving improper and potentially dangerous treatment.
To help address this issue, The Pew Charitable Trusts conducted research on several strategies to improve patient matching rates. The research, compiled in a report released on Oct. 2, examined the potential of biometrics and other unique identifiers, patient-empowered approaches, data standardization, and the use of data from third-party sources to address this problem.
Pew hosted a panel at its Washington office on Oct. 2, 2018, where experts on patient matching and technology discussed the report’s findings and how different approaches offer a path forward to ensure that patients’ records are accurately linked wherever they seek care.
Shaun Grannis, director, Regenstrief Center for Biomedical Informatics
Mark LaRow, chief executive officer, Verato
Robert Rudin, information scientist, RAND Corporation
Catherine Schulten, vice president of product management, LifeMed ID
Joe Trelin, senior vice president of product and corporate development, CLEAR
Micky Tripathi, president and chief executive officer, Massachusetts eHealth Collaborative
Rita Torkzadeh, officer, The Pew Charitable Trusts
Moderator: Ben Moscovitch, project director, The Pew Charitable Trusts
Resources for federal, state, and local decision-makers
Data-driven state policy innovations across America