Patient duplicates and patient matching are a challenge throughout the healthcare industry. As technology solutions – especially those that are automated – increasingly become critical to healthcare operations, managing patient identification, linking, and reducing duplicates is critical. While some have proposed a national medical identifier, it is likely – if it were to occur – far off and is probably not something that organizations should count on. Reducing duplicates is not just something to be done for the sake of reporting accurately or having clean data, it is – in fact – a patient safety issue. If two patients are merged incorrectly or two separate records exist for one individual, clinicians may lack the information needed – e.g., an accurate medication or allergy list – to ensure that adverse events do not occur.

This leaves medical practices and other healthcare organizations with only processes and existing technologies to manage this challenge. For larger healthcare organizations, it probably makes the most sense to invest in an eMPI or Enterprise Master Person Indexing system. This allows an organization to send identifying information from multiple systems to the eMPI and have the eMPI link the data sources and create a unique identifier. eMPI systems also often have the tools to manually reconcile difficult cases and to manage incorrect matches – i.e., undo linkages that were created in error. An example of this would be if twins were assumed to be the same individual, linked in the eMPI and then it is realized that the twins are separate individuals. Downstream systems would, however, also have to have the capacity to process these reverse linkages in their systems. Downstream systems would also have to merge duplicated patients. EMRs and other systems used by medium and large healthcare enterprises often have such features and healthcare systems – especially those with heterogenous EMR environments – have been making use of eMPIs for a long time.

One unique eMPI product is Verato. This product operates entirely as a service, and, therefore, it does not require any infrastructure – e.g, servers, databases – to be maintained for the sake of managing the eMPI. Rather, their clients simply access Verato’s API (Application Programming Interface), send demographic information, and receive back a unique identifier. Thus, eMPI as a service, however, is not the most unique development in the eMPI realm that Verato has brought to enterprises. The company uses what is called referential matching. They have built a large repository from various data sources on hundreds of millions of residents in the United States and that data is used to even further reduce the duplicate rate and inappropriate merging rate in an enterprise’s environment. Traditionally, users of eMPIs had to rely solely on the data that they collected to link various data sources. Referential matching, however, allows them to use other large data sources (examples include public data, credit bureau or financial data, etc…) to perform highly accurate linkages. As data aggregation further becomes part of everyday life, it is likely that such services will continue to evolve, grow, and become more ubiquitous in healthcare (as well as other industries).

Smaller medical practices and healthcare organizations are likely to neither have the capital nor the in-house expertise to purchase, implement, and maintain an eMPI system. That said, they are also likely to have fewer systems and thus a reduced likelihood of systemic issues arising due to patient duplicates or inappropriate linkages. Nevertheless, patient safety issues can still arise due to patient matching issues. A small practice can reduce the likelihood of this occurring by enacting rigorous data management policies. For example, the practice should set a standard on identification – e.g., are you going to use the name of the individual as written on their insurance card or license? The latter is probably more static as individuals can change health plans frequently. There should also be steps taken to ensure that a patient doesn’t exist in a system before creating a new record – e.g., checking by name, previous names, date of birth, etc… Additionally, steps should be taken to check archived or inactivated records before creating a new record. It is not sufficient to trust the patient’s memory. Before creating a new record, check the archived or inactivated records and reactivate one of those rather than creating a whole new chart. These processes should be documented and all employees handling patient records ought to be trained and held accountable for following them.

In addition to these processes, most ambulatory EMRs have some sort of patient merging and unlinking features. These features should be restricted to only highly trained personnel and used only after a careful review has occurred. These are powerful tools that can assist in recuperating from issues, but if they are opened up or used too frequently, other data management issues could arise.

Patient matching and duplicate prevention are perennial healthcare issues. Large organizations can take advantage of their scale to implement an eMPI and even investigate innovative eMPI solutions such as Verato; whereas, smaller organizations must rely on processes, procedures, and their EMRs intrinsic capabilities to prevent and recover from patient matching errors.


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