The topic of patient identity and patient matching has been around as long as healthcare has. It is a critical component of clinical data integration, clinical data migration, and health information exchange. That said, the idea of a unique patient identifier is not new either. In fact, there have been petitions to support addressing the issue, such as that as part of AHIMA’s MyHealthID advocacy campaign, as well as crowd-sourced initiatives, including CHIME’s funding of a patient identification concept contest. As part of their efforts, the Sequoia Project published a white paper, A Framework for Cross-Organizational Patient Identity Matching, on this topic. Most recently, Experian believes it’s wealth of credit bureau data makes it the perfect private-sector innovator for patient ID’s.
According to Dan Johnson, Executive Vice President of strategy for Experian Health, the company doesn’t charge healthcare systems for its Universal Identity Manager, which relies on a combination of probabilistic and referential matching, rather than deterministic matching. “We need to give this away,” Johnson said. “We realized that we almost have to seed the market with this and remove the financial barrier to adoption.”
Experian’s implementation pipeline includes more than 100 heath systems, some payers and pharmacies, and the company is in talks with Epic Systems Corp, Cerner Corp, and other vendors to incorporate the ID into their systems. It also has worked with Congress on the Ensuring Patient Access to Healthcare Records Act, which removes the business associate status from clearinghouses, thereby allowing them to use protected health information under HIPAA.
That said, the timing couldn’t be any worse, with Equifax’s recent breach, where the personal information including driver license numbers and social security numbers, of 143 million Americans were compromised. Experian itself suffered a massive breach in 2015. Should the private sector – specifically credit bureaus – conceivably be entrusted with critical personal information that leaves consumers – and in this case, patients – at risk? Doesn’t this seem like a problem better solved by the public sector?
Whether its best solved by the private or public sector, the monetary incentives are huge. According to an AHIMA survey, more than half of health IT management professionals regularly work on resolving patient matching and duplicate patient record issues. According to an ONC report, each case of mis-identification at the Mayo Clinic costs at least $1,200. Intermountain Healthcare spends between $4 million and $5 million per year on technologies and processes intended to ensure correct patient identification.
Todd Rogow, Senior VP & CIO, recently elaborated on how labor-intensive patient identity can be:
“When I joined Healthix two and a half years ago, I observed that we were losing ground because we were getting 11K new potential patient matches every day that required manual review. With such a high volume, we couldn’t possibly keep up using a manual approach. To automate the process, we contracted with Verato, a company that has a service that does something unique. They realized a while ago that there are a lot of public records for Todd Rogow. For example, I have an electricity bill, so there’s a public record of me and my address. There could be a credit agency that also has my name and my address and could include other things like a social security number, home phone number, or my date of birth. All of this is publicly available. They built an application that we reach out to as a service through an API, and we provide two identities for who we think may be the same person. We’re not certain, so we reach out to them and we ask them to query their public datasets from credit agencies, public utilities, etc., and come back with a recommendation on identity matching.”
More than the monetary impact, it’s a SAFETY issue. Consider the statistics published through the years from key healthcare organizations like CHIME, HIMSS, and AHIMA.
- 8-12% of hospitals’ medical records are duplicates
- On average: 64,000 – 96,000 medical records in an EMR (system) refer to a patient with another existing medical record
- The average cost associated with repeated medical care – $1,009
- Kaiser Permanente of Southern California has over 10,000 records of people named Maria Gonzales
- HIMSS: 8-14% of medical records include erroneous information tied to an incorrect patient identity
All said, barriers to developing a National Patient Identifier persist. Congress continues to ban federal funding to develop an NPI and tech vendors are reluctant to share their proprietary information for fear of losing market share. How can we begin to solve for patient data interoperability and health data exchange if we can’t efficiently and effectively identify which patient the data belongs to? Is the government best-suited for providing a solution to this issue or are we to expect the private sector to solve? One thing is for sure, there is going to be reluctance to credit agencies involvement in developing a solution given recent track record.