The need for a universal means to accurately and efficiently match patient ID’s and patient biometrics across healthcare is well documented in both health information technology and health management literature.
In 2017, The College of Healthcare Information Management Executives described it as a “serious problem,” and in 2015 it stated that “unintended injury attributable to patient data-matching error is a considerable and growing problem in this era of health information exchange… Despite years of development, no clear strategy on patient matching has emerged.”
In February 2018, the New England Journal of Medicine made the following claim in an article published on its website:
“Developing a unique patient identifier system would have many benefits. When accurate information is attached to the right patient, data access is timelier for clinical, administrative, quality improvement, and research purposes; inappropriate care, redundant tests, and medical errors are reduced; and health information exchange becomes easier — within organizations as well as between. Identifiers are also beneficial for patient mobility, allowing information to be linked to patients and following them as they move.”
Extensive time and effort are spent during the patient registration process to gather patient identity information. It is particularly difficult and time-consuming to gather enough information with each transaction to match patient ID’s across master patient indexes (MPI's) to the level of accuracy required by insurance, pharmacy, and clinical systems. This represents significant redundancy of effort, risk of error, and loss of time by patients and healthcare providers alike.
In fact, the patient registration and identity verification process, which is central to every episode of healthcare delivery, is one of the most pervasive, time-consuming, labor-intensive nonclinical efforts undertaken by healthcare providers. Those processes continue to be among the most dominant and inefficient support processes in healthcare.
The matching of Patient ID’s across healthcare transactions is essential to many core healthcare functions including billing, private information exchange, and authorization for treatment or procedures.
Current health IT systems rely primarily upon demographic data such as name, birth date, and billing addresses to match Patient ID’s. This strategy matches Patient ID’s with 90 to 95 percent accuracy, but, scaled to population, results in unacceptably high numbers of duplicate but inconsistent records that need to be corrected or merged, with high risk for error that has the potential to negatively impact medical outcomes.
According to the Rand Corporation, the “lack of a [universal patient identifier] prevents the health care system from achieving full automation and connectivity and its full clinical, public health, and research potential because it is dependent on non-ambiguous linking of patients and records.” In fact, Rand Corporation has estimated that effective private health information exchange between healthcare providers would realize more than $77 billion in efficiency savings alone and potentially more than double this figure in terms of improved clinical outcomes and patient safety.
Recent efforts to adopt sophisticated electronic health records systems (EHR's) and drive system interoperability have been inefficient and inaccurate in matching Patient ID’s across multiple independent enterprise MPI's. Numerous entities have sought to solve the Patient ID problem specifically. They have failed to solve the problems of time consumption, inefficiency, and introduction of Patient ID errors that continue to plague healthcare.
Early proponents of assigning each patient a unique numerical identifier failed to overcome objections that such an identifier would potentially expose patients to hacking, fraud, and unacceptable risk that private data might be compromised. Accordingly, in 1998, patient privacy advocates lobbied Congress to pass Public Law 105-277, which prohibits the Department of Health and Human Services from allocating federal government resources to “promulgate or adopt any final standard… providing for the assignment of a unique health identifier for an individual… until legislation is enacted specifically approving the standard.”
In 2017, the College of Healthcare Information Management Executives (CHIME) recognized patient identity as a “serious problem in healthcare” (Siwicki). According to the American Health Information Management Association, the average medical record duplication rate is between 8 and 12 percent. Accordingly, CHIME sponsored an industry-wide competition for the purpose of “incentivizing innovators to create a solution for ensuring 100 percent accuracy in identifying patients in the U.S.” (Siwicki).
The College of Healthcare Information Management Executives (CHIME) Healthcare Innovation Trust considered accurate patient identification “fundamental to patient care today.”
As such, CHIME hosted a $1 million National Patient ID Challenge in 2016 to stimulate the creation of a “nationwide patient identification solution.” It set extremely high standards for the contest in terms of potential situations and use cases. No contestant was able to clear all of the hurdles.