Is Your Organization Making Avoidable Patient-Matching Errors?

April 28, 2021
This piece offers insight into how to fix these preventable mistakes

Imagine this: Three people named Shaun, Shawn, and Sean walk into a hospital. While this may sound like the start of a joke, it’s no laughing matter. If seemingly harmless clerical errors were to take place, this could jeopardize the accuracy of downstream patient matching.

When an electronic health record (EHR) receives a misspelled name, or a duplicate record gets created, there could be misunderstandings about medications, miscommunication of follow-up instructions, or delays in care. The result of miscommunication between caregivers during patient transitions can include readmissions, patient harm, or inadequate informed consent. Research from CIRCO Strategies indicates that such communication failures have led to nearly 2,000 preventable deaths and $1.7 billion in malpractice costs.

Patients today often receive care at multiple facilities operated by different healthcare organizations, and patient records are left scattered. Not only is poor patient matching a healthcare risk, it also raises costs. A Black Book survey of enterprise master index users found that services repeated because of duplicate records cost on average $1,950 for each patient per hospital stay, amounting to $1.5 million per hospital. This same study found that 18 percent of sample EHR records were duplicates.

To improve healthcare outcomes for patients and reduce costs for providers and payers, we need to improve patient matching. In Maine, HealthInfoNet leverages the Master Data Management expertise of Audacious Inquiry, a health IT company that facilitates the secure transmission of event-driven data to identify and proactively address several patient matching challenges, and the IBM Initiate Master Data Service software, which is integrated into HealthInfoNet’s Health Information Exchange (HIE) software platform.

Here are some lessons learned and key opportunities organizations should consider in order to achieve more seamless clinical data exchange:

1. Involve patients in their data validation at registration. Hospitals are facing significant challenges on all fronts during the COVID-19 pandemic, including financial losses that have led to staffing furloughs and layoffs. Administrative and non-clinical employees are often the first to be let go in these staffing changes, but they are vital members of the team, and we need them to accurately input patient data and provide quality control. Without accurate records, patient matching is impossible to execute. Simple steps, such as asking patients to confirm information at registration or providing kiosks where they can check their records and correct details, are quick yet effective steps to move us closer to accurate records for everyone.

 2.  Establish cohesive data governance. All health systems and their IT vendors need to use the same terms, definitions, and processes while compiling patient records. Interoperability – and the more efficient care it leads to – is possible, but we need effective structures in place to make this a reality.

 3.  Commit to technology investments. To improve existing patient matching systems, health systems and IT vendors must invest in technology tools that can catch and correct errors and identify duplicate records using deterministic and probabilistic matching algorithms. These capabilities continue to evolve, and a true commitment to improved patient matching requires an ongoing investment.

4.  Establish strong partnerships. Build an expert team that can tackle these daunting matching challenges. Local, state and national HIEs are responsible for moving vital healthcare patient data between different facilities and providers benefit from our collaboration with partners that have deep data management knowledge.

With CMS’ Conditions of Participation real-time data exchange requirements set to take effect on April 30 for Medicare and Medicaid-certified hospitals and critical access hospitals, health systems should be prepared to address increasing patient matching challenges head-on, as the volume of clinical data is about to increase significantly. 

While record accuracy and patient matching will always be a moving target, it is possible to make it so everyone, whether their name is Shaun, Shawn, or Sean, receives the right healthcare services at the right time.

Shaun T. Alfreds is the Executive Director and CEO of HealthInfoNet, an independent, nonprofit information services organization that manages the statewide HIE in Maine.

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