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The Benefits of an EMPI, Multi-Domain MDM Strategy
Jul 07, 2021
In our earlier blog, we discussed why having a multi-domain Master Data Management (MDM) approach tied to an Enterprise Master Patient Index (EMPI) is important for health systems to properly identify and determine patient matches when their data is coming from different systems.
When determining a patient match, EMPI applies both probabilistic and deterministic matching algorithms. Deterministic matching, or exact match logic, looks for a precise match of the data elements in a patient record. For example, two records will match if they agree on elements such as the patient's first and last name and Social Security Number. Elements that do not match exactly, such as a nickname or maiden name, will likely be rejected.
Probabilistic matching ranks different data elements based on preset levels and scores the likelihood that two or more records belong to the same patient. The higher the score, the greater probability that they are in fact a match.
When users use both EMPI and MDM together, the accuracy of their match improves drastically. This is achieved by using EMPI Referential matching along with customized match rules and algorithms built into MDM, so that the system creates a “best-of-breed” patient record. This record provides the user a higher level of confidence that the match is accurate and reduces the manual remediation process.
When there’s a match between two patient profiles, the EMPI evaluates the matching scores, determines if two profiles are a match, and assigns a unique identifier. This matched profile is then sent to the health system for linking the patient profile and consolidating the duplicate data.
EMPI matches are very trustworthy and offer users unique identifiers to properly link duplicate patient profiles and the medical records to a single profile. This reduces data redundancy and improves the accuracy of patient care.
In some instances, the result of a Referential Match leads to a potential match between two patient profiles. When this happens, EMPI sends the potential match to the MDM or the health system’s data steward for remediation.
To illustrate, we have two sets of patient data: One for “John Smith” and another for “Joan Smith,” who have the same address, the same last name, the same gender, but different first names. The EMPI will call this out as a potential match and will not assign a unique identifier.
To handle such data scenarios, like the health system in our earlier blog did, users should send the unresolved/potential match patient records from the EMPI directly to the MDM and resolve such data anomalies using MDM advanced match capabilities or use a manual reconciliation process.
Another real-life example of this is when health system handle matches for newborns, who might not yet have a name which is not stored in the EMPI referential data repository. With this type of situation, often the hospital will give the newborn the name “Baby Girl appended with the mother’s name,” (e.g., “Baby Girl Kelly Thompson”) indicating that the patient is a newborn. In this scenario, the EMPI will assign a unique identifier to the patient profile and send it back to the system to receive an update when a name is given to the baby. In MDM, the newborn will be created as a new patient and will be associated with the parent profile creating a household hierarchy between the parent and the newborn.
Bringing EMPI and MDM data matching capabilities together can enrich and consolidate the health system’s data, providing a 360-degree analytical insight to drive business decisions and improve the accuracy and efficiency of patient care. As a result, the benefit of having EMPI and MDM working together is that it enhances the accuracy of a match.
IQVIA understands the importance of helping organizations manage their complex data elements. We can help clients implement MDM and EMPI strategies that allow them to better manage their data. Let us know how we can help.