--- title: "The Problem of Patient Matching: New Pew Report Details Recommendations" description: In the pursuit of value based care, interoperability is key. But is it achievable in the current healthcare landscape? And if not, what would we have to do to bridge that gap? image: https://blog.healthmonix.com/hubfs/Stock%20Images%201200%20x%20628/grandma.jpg --- ![logo-light](https://blog.healthmonix.com/hubfs/logo-light.png "logo-light") - [Who we help](https://healthmonix.com/who-we-help/) - [Overview](https://healthmonix.com/who-we-help/) - [ACOs](https://healthmonix.com/acos/) - [Health systems](https://healthmonix.com/health-system/) - [Healthcare technology](https://healthmonix.com/healthcare-technology/) - [Physician practices](https://healthmonix.com/physician-practice/) - [Health system VPs](https://healthmonix.com/health-system-vice-presidents/) - [Chief financial officers](https://healthmonix.com/chief-financial-officers/) - [Chief medical officers](https://healthmonix.com/chief-medical-officers/) - [Chief quality officers](https://healthmonix.com/chief-quality-officers/) - [ACO executive directors](https://healthmonix.com/aco-executive-directors/) - [Solutions](https://healthmonix.com/prism/) - [MIPSpro](https://healthmonix.com/product/mips-pro/) - [Cost](https://healthmonix.com/product/cost/) - [ACO Impact](https://healthmonix.com/product/aco-impact/) - [Analytics](https://healthmonix.com/product/analytics/) - [Ambulatory Specialty Model](https://healthmonix.com/ambulatory-specialty-model-asm/) - [TEAM](https://healthmonix.com/team-program/) - [HealthConnect](https://healthmonix.com/health-connect/) - [Data integration](https://healthmonix.com/dataintegration/) - [Consulting](https://healthmonix.com/consulting-services/) - [Score optimization](https://healthmonix.com/score-optimization/) - [Patient matching](https://healthmonix.com/patient-deduplication-and-matching/) - [Outcomes](https://healthmonix.com/outcomes/) - [Company](https://healthmonix.com/company/) - [Our story](https://healthmonix.com/company/) - [Team](https://healthmonix.com/team/) - [Careers](https://healthmonix.com/healthmonix-careers/) - [Resources](https://healthmonix.com/resources/) - [Help and support](https://healthmonix.com/customer-support/) - [Healthmonix Advisor](https://blog.healthmonix.com/) - [Webinars](https://healthmonix.com/our-webinars/) - [Educational resources](https://healthmonix.com/mips-education/) - [Help and support](https://healthmonix.com/customer-support/) - [Contact us](https://healthmonix.com/contact-us/) - [Measures](https://healthmonix.com/mips-measures/) - [Quality](https://healthmonix.com/mips-measures/mips-quality-measures/) - [CMS specialty sets](https://healthmonix.com/cms-mips-specialty-measure-sets/) - [Promoting Interoperability](https://healthmonix.com/mips-measures/mips-promoting-interoperability-measures/) - [Improvement Activities](https://healthmonix.com/mips-measures/mips-improvement-activities/) - [Cost](https://healthmonix.com/mips-measures/mips-cost-performance-category/) - [Log in](https://healthmonix.com/login/) # Healthmonix Advisor # The Problem of Patient Matching: New Pew Report Details Recommendations Posted by [Christina Zink](https://blog.healthmonix.com/author/christina-zink) on October 11, 2018 ![](https://app.hubspot.com/settings/avatar/1e386ff4e65c2b2e78f1dd6f6c67a86d) Find me on: [LinkedIn](https://www.linkedin.com/in/christina-zink-062b4457) - [Tweet](https://twitter.com/share) ![grandma](https://blog.healthmonix.com/hubfs/Stock%20Images%201200%20x%20628/grandma.jpg) In the pursuit of value based care, interoperability is key. But is it achievable in the current healthcare landscape? And if not, what would we have to do to bridge that gap? These questions are partially explored in a new report from [The Pew Charitable Trusts](https://www.pewtrusts.org/en/research-and-analysis/reports/2018/10/02/enhanced-patient-matching-critical-to-achieving-full-promise-of-digital-health-records) that digs into the problems surrounding patient matching (a major factor in interoperability), traces recent progress, and recommends important next steps to take as the industry works toward improvement. As the report’s researchers explain: “Once these recommendations are implemented, clinicians and patients can have more assurance that EHRs contain complete, accurate, and up-to-date medical information—thus improving safety, reducing costs, and better coordinating care for individuals who see multiple medical professionals.” To create its report, Pew commissioned research, examined public information, conducted focus groups with patients, and communicated with hospital executives and other experts.   #### **Patient Matching** Patient matching, as the report explains, is “the capacity to successfully search each individual’s record in disparate locations and know that it refers to the correct person.” Patient matching rates vary widely; in some cases, the failure rate is as high as 50%. Organizations can achieve match rates of 90% or higher, though, if they maintain high data quality and manually check and fix uncertain matches. This can be extremely dangerous for patients, as Pew illustrates by referencing the results of a 2012 CHIME survey wherein 1 in 5 hospital chief information officers indicated that patients had been harmed in the previous year due to mismatches. It can also be costly: as the researchers explain, “In an extreme example, the care for an 11-month-old twin was documented in her sister’s record, resulting in the failure of the health system to recoup $43,000 in costs from the insurer.”   #### **Near-term Recommendations** To combat this serious barrier to interoperability, Pew identifies three key requirements for a nationwide strategy: 1. Coordination on a national level in order to identify needed best practices, 2. Commitment from both the healthcare and technology sectors to implement these best practices, and 3. Patient involvement. Pew also concluded that there is no solution currently that can achieve perfect or near-perfect match rates for all patients, but there are practical steps that organizations can take to improve these rates in the near-term. Pew offers the following recommendations for near-term improvement: - Clarification of restrictions on government funding for unique identifiers - Agreement on demographic standards - Assessment of privacy ramifications - Further research on / adoption of referential matching where third-party data are used - Verification of phone numbers and other identifying information provided by patients to reduce the likelihood of typographical, data-entry, or clerical errors   #### **Long-term Recommendations** Pew found that despite the near-term opportunities for improvement listed above, the only way to ensure meaningful long-term improvement will be to adopt entirely new approaches and technologies. They offer the following long-term recommendations: - Entrusting a single organization to oversee a nationwide patient-matching strategy - Launching pilot projects for patients to use their smartphones to help match records - Determining the infrastructure and standards necessary for using biometrics and other technologies for effective, secure matching (while protecting privacy). 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