Referential Matching: Fixing the Problem of Duplicate Patients

referential matching

Seeing Double

An article by Bruce Pegg of highlights a very real problem in the medical billing industry and one way we may be able to avoid it. Many doctor’s offices and medical billing companies deal with the issue of a patient being entered into the system twice. This can arise from a variety of issues, such as name and address changes between visits. A duplicate patient entry can create a knock-on effect that can impact everything from billing to adequate patient care. Furthermore, denials caused by miss-identification can cost hospitals and other providers over a million dollars a year. 

How effectively does EMR catch duplicates?

The current solution to this conundrum has been found within the system of EMR. Pegg explains that “in most EMRs, a built-in module, known as a master patient index (MPI), uses an algorithm to look for records that may possibly belong to the same patient.” This module essentially compares the data, identifying when two records are identical in some respects and highlighting the deviations. However, this system is limited in its scope, often missing duplicates where data is missing entirely or situations like name changes.

How can Referential Matching fill the gaps?

Referential matching seeks to make up for those shortcomings. This system would use a consistently maintained and updated HIPAA compliant database. Data would no longer be cross referenced by a single EMR. Instead, referential matching can be applied to an existing EMR or records database to pinpoint duplicate data. Pegg goes on to add that “referential matching also can automatically resolve duplication errors within and across EMRs. And it can provide insights into how data entry is creating the duplicate entries to begin with.” An accessible pool of patient data that is regularly updated may be the next best step in ensuring quality medical records keeping.  

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