Harris Data Integrity Solutions, the leading provider of best-in-class patient data integrity services and software, has released a white paper that undertakes an in-depth examination of the healthcare industry’s chronic people matching problem. In addition to dissecting the challenges and impacts patient misidentification has on care safety, outcomes, and costs, People Matching in Healthcare: Challenges, Impact and Solutions explores efforts underway on multiple levels to identify a system-wide resolution to the problem.
“The tumultuous state of patient matching exposes patients to duplicative and unnecessary testing and services and care delays, exacerbates fraud risks, impacts public health emergency response, and costs the U.S. healthcare system over $6 billion annually in denied claims,” said Lora Hefton, executive vice president of Harris Data Integrity Solutions. “But the future is not as grim as the present might indicate, as our research also found that efforts to identify the right path forward are finding a foothold as stakeholders from across the healthcare continuum come together to remove obstacles and implement effective solutions.”
In People Matching in Healthcare: Challenges, Impact and Solutions, Harris Data Integrity Solutions’ patient identity experts highlight the efforts of Patient ID Now to eliminate legislative barriers hindering exploration of a unique patient identifier, and the collaborative’s work to establish the framework of a national strategy for effective patient identification and matching. They also look at the work undertaken by the Project US@ collaboration, spearheaded by the Office for the National Coordinator (ONC), that resulted in a technical specification for collection of patient addresses, and AHIMA for its related companion guide with operational guidance and best practices.
The white paper also explores the important role the right technology plays in eliminating the patient matching problem at the organizational level – a problem that has helped drive the average duplicate record rate to 18%. The ideal technology solution enables protection across the entire master patient index (MPI) and electronic MPI (EMPI) by operating in multiple environments and at multiple stages throughout the patient record process.
“What is needed is an end-to-end protection model centered on technology capable of catching mismatches and errors upfront and identifying and resolving duplicate and overlaid records, eliminating rather than adding to the patient identification problem,” said Hefton. “People Matching in Healthcare describes what that model looks like and provides insights into why the typical EHR system is incapable of addressing the mismatch issue on its own.”
People Matching in Healthcare: Challenges, Impact and Solutions is available for download here.