A National Patient Identifier Is Up for Debate. Patient Safety Is Not

By Jessica Welch and Mark Erwich

Knowing a patient’s medical history is a fundamental part of delivering quality care. Unfortunately, identifying a person, even within the same hospital system, is not as straightforward as it may seem. Misspellings, address changes, maiden and married names, and many other factors make it difficult to match people to their medical records. In fact, the accuracy of matching patients to their records can be as low as 80% within a single care setting and as low as 50% among organizations that share electronic health information (Pew Charitable Trust, 2018).

This lack of consistency in patient identification leads to medical errors and financial burdens for patients, clinicians, and institutions. Repeated medical care due to duplicate records costs an average of $1,950 per inpatient stay and over $1,700 per emergency department visit. According to Black Book Research (2021), 35% of all denied claims result from inaccurate patient identification, costing the average hospital $2.5 million and the U.S. healthcare system over $6.7 billion annually.

Errors in patient identification can have dire consequences: unnecessary testing and treatment, delayed diagnosis, and even death. Accordingly, patient identification is a significant topic in the healthcare industry. The Joint Commission (2023) has listed “Identify patients correctly” as a goal in its annually published hospital National Patient Safety Goals since the inception of the goals in 2002 and continues to do so.

Medical errors due to wrong-patient incidents can be difficult to quantify due to the wide variety of possible outcomes, but they may happen more often than currently assumed. In a report by the Ponemon Institute, 64% of surveyed healthcare executives reported that patient misidentification errors happen more frequently than the reported industry standard of 8%–10% (Imprivata, 2016). In fact, an analysis of reports from the Veterans Health Administration shows that 182 of 253 errors were attributed to patient misidentification (Dunn & Moga, 2010).

The answer to misidentification issues seems clear: Make it easier to share and manage patient data across health organizations. For more than 20 years, various groups have advocated for the adoption of a unique national patient identifier. Such a solution was initially proposed as part of the Health Insurance Portability and Accountability Act (HIPAA), which was passed by Congress in 1996. Yet since then, Congress has dug in its heels by retaining restrictive rider language in budget appropriations that prevents the adoption of a unique identifier strategy.

Without a uniform approach for managing patient identities, organizations commonly identify patients by using algorithms to sort through demographic records and make matches. However, continued digital transformation has made identity management increasingly difficult. No longer are records matched in only one system; most healthcare organizations now have software to enable digital front doors, customer relationship management systems, consumer and third-party data vendors, and many other data sources in their healthcare IT (HIT) stack.

COVID-19 further highlighted the need for matching across applications. During the beginning of the pandemic, healthcare organizations worked quickly to meet patient needs with new tools such as telehealth applications. But not only did organizations expand their HIT systems, care journeys also became more complex. For example, a patient might have received treatment at a hospital as well as at an affiliated clinic using a different electronic health record (EHR). Matching identities across applications and locations became a challenging part of delivering care.

In parallel, innovative healthcare providers have worked with IT companies to address the issue of patient identity. Significant progress has been made with commercially available solutions that match person records both within EHRs and across disparate sources in healthcare organizations.

In the United States, 60% of people live with at least one chronic disease (CDC, n.d.) and life expectancy is falling (Rakshit et al., 2022), so delivering quality care is of utmost importance. Unfortunately, a survey commissioned by the American Board of Internal Medicine (ABIM) Foundation found that trust in physicians decreased during the COVID-19 pandemic and concluded that a rebuilding of trust is needed (ABIM Foundation, 2021). To start that process, healthcare organizations must know the basics—whom their patients and members are and what their care journey looks like. While discussions around a unique patient identifier continue, the healthcare industry must act now and explore commercial partners to address the needs of the patients, members, and clients in its care.

Widely available identity solutions include master person index (MPI), enterprise person index (EMPI), and master data management (MDM) models. EHR systems often have basic matching capabilities that may include an MPI. However, MPIs are usually based on deterministic logic that struggles to overcome inconsistent data. As healthcare operations become more complex and include more data from disparate sources, such as consumer, marketing, and third-party data, more effective solutions are needed to connect information from a variety of sources.

EMPIs are more advanced stand-alone solutions that can be hosted on premises or in the cloud. These systems are based on advanced algorithms that are better suited to match unique patient populations. Still, EMPI solutions frequently struggle to connect out-of-date, incomplete, or ambiguous data. While EMPIs match data, MDM solutions can manage data in a central location and are better suited to identifying, linking, and synchronizing data from different sources. But because most MDM solutions are generic systems that can be used in any industry, they require extensive tuning to meet the unique needs of healthcare organizations.

Unlike generic MDM solutions, healthcare master data management (hMDM) is built specifically for organizations in the healthcare space. An hMDM platform can manage identities of patients, members, providers, consumers, citizens, and employees with one solution—without the need for extensive tuning to meet healthcare-specific safety, security, and business needs. When practitioners can see a patient’s entire care journey, it reduces the risks of medical errors. In addition, reducing patient misidentification incidents lowers the rate of denied claims and duplicate procedures. It also improves initiatives such as digital front doors, outreach efforts, and overall patient engagement and experience.

When healthcare organizations utilize enrichment data, including social determinants of health, healthcare providers can see critical factors beyond a patient’s clinical history and better treat the whole person. Healthcare leaders also become empowered to see trends across communities and demographics, which allows them to address health inequities and support vulnerable populations.

Jessica Welch works in public sector at Verato. Mark Erwich is chief marketing officer at Verato.

References

ABIM Foundation. (2021, May 21). Surveys of trust in the U.S. health care system. https://www.norc.org/PDFs/ABIM%20Foundation/20210520_NORC_ABIM_Foundation_Trust%20in%20Healthcare_Part%201.pdf

Black Book Research. (2021, August 27). Improving the patient identification process and interoperability to decrease patient record error rates. https://www.blackbookmarketresearch.com/blog/improving-the-patient-identification-process-and-interoperability-to-decrease-patient-record-error-rates

CDC. (n.d.). About chronic diseases. https://www.cdc.gov/chronicdisease/about/index.htm

Dunn, E. J., & Moga, P. J. (2010). Patient misidentification in laboratory medicine: A qualitative analysis of 227 root cause analysis reports in the Veterans Health Administration. Archives of Pathology and Laboratory Medicine, 134(2), 244–255. https://pubmed.ncbi.nlm.nih.gov/20121614/

Imprivata. (2016). 2016 national misidentification report. http://promos.hcpro.com/pdf/2016-national-report-misidentification-report.pdf

The Joint Commission. (2023). 2023 Hospital National Patient Safety Goals. https://www.jointcommission.org/-/media/tjc/documents/standards/national-patient-safety-goals/2023/2023-hap-npsg-goals-102122_simple.pdf

Rakshit, S., McGough, M., Amin, K., & Cox, C. (2022, December 6). How does U.S. life expectancy compare to other countries? https://www.healthsystemtracker.org/chart-collection/u-s-life-expectancy-compare-countries/

Pew Charitable Trust. (2018, October 2). Enhanced patient matching is critical to achieving full promise of digital health records. https://www.pewtrusts.org/en/research-and-analysis/reports/2018/10/02/enhanced-patient-matching-critical-to-achieving-full-promise-of-digital-health-records