- In a new report sponsored by Pew Charitable Trusts, RAND identified ten potential patient EHR matching solutions and proposed a three-stage approach to help resolve the healthcare industry’s decades-old problem with patient matching accuracy.
“Incomplete and erroneous record matching (the process of identifying and linking medical records for the same patient across different data sources) is a widely recognized problem that impedes interoperability and health information exchange (HIE) among health care providers, increases health care costs, and hampers health care quality,” stated RAND in the report.
The 110-page report focuses specifically on patient-empowered approaches to EHR matching that include additional, voluntary roles for patients extending beyond simply providing demographic information.
RAND investigated potential patient-empowered EHR matching solutions and identified a single, three-stage patient EHR matching solution that combines aspects of several different patient matching strategies.
“While we did not identify a ‘silver bullet’ solution, we did identify multiple patient-empowered approaches that may have potential — with further development — to improve record matching,” wrote RAND.
“Ultimately, we selected a three-stage solution in which patients can “verify” their mobile phone number and other identity attributes with their health care providers and use new smartphone app functionalities that enable bidirectional communication of identity and health information between patients and providers,” authors continued.
The report explored the following 10 patient EHR matching solutions:
- Implementing a voluntary universal identifier.
- Using a public key as an identifier.
- Expanding the use of existing government-issued identifiers.
- Adding knowledge-based identity information.
- Adding biometric data.
- Having patients verify identity information.
- Using consumer-directed exchange.
- Using health record banks.
- Having patients manually verify record matches.
- Having patients supply record location information.
RAND assessed the effectiveness of each identified solution based on 11 evaluation criteria.
Criteria included sustainability, feasibility of development, pilot testing and implementation, minimal security risks, political viability, potential to foster new uses of matched records, low potential for unintended negative consequences, likelihood of adoption, improvement in record matching if widely implemented, and degree of patient control.
“The large number of criteria reflects the complexity of the record matching design space and the potential need for nuanced tradeoffs,” wrote report authors. “This complexity is also apparent in the ongoing challenges with record matching, the diverse potential solutions we identified, and the lack of clear consensus among experts on a favored solution.”
RAND drew from these potential solutions to create the single three-stage approach recommended for development and pilot testing.
The think tank also issued three recommendations to advance the approach through development and testing.
First, RAND recommended developing technical specifications for verified data fields, developing best practices that allow healthcare providers to verify phone numbers, and pilot testing and refining specifications and best practices to maximize feasibility and usability.
RAND also advised developing application programming interfaces (APIs) and best practices for establishing bidirectional communication between a smartphone app and healthcare provider registration systems at the point of care. Developers would pilot test and refine these APIs.
Finally, the think tank suggested developing advanced app functionalities to further improve record matching and increase the value of apps to patients and providers.
To accelerate the solution’s development, RAND further advised stakeholders establish or designate an organization to oversee national progress in patient EHR matching and conduct more rigorous research into the nature and magnitude of EHR matching errors.
Creating methods for healthcare providers to objectively benchmark their EHR matching performance would also help to accelerate progress in improving patient matching accuracy.
“Given high uncertainty as to the extent to which any specific solution can ultimately succeed in improving record matching, further investigation, development, and pilot testing of a range of solutions are warranted,” report authors concluded.