EMPI (Enterprise Master Patient Index) is a consolidated hub of all patient related information that would act as a single source of truth.
Hospitals have various departmental systems such as lab systems, radiology systems, EMR systems and other Health Information systems that operate in isolation. Typically patient data is spread out across these disparate systems and it is challenging to have a 360-degree view of the patient.
Hence, hospitals create an EMPI hub that assigns a unique ID to each patient. EMPI systems use algorithms to match and link records across disparate systems. The algorithms also identify duplicate records and reduce the number of false negatives. The typical attributes used by the matching algorithms are first name, last name, DOB, sex, social security number, address and more. The matching algorithms (deterministic, probabilistic/fuzzy) must consider typos, misspellings, transpositions, aliases, etc.
Besides the internal attributes, many organizations also source data from external third parties (e.g. Equifax) that can be used for increasing the accuracy of the matching engine. This is helpful as people change addresses, phone numbers, etc. with time.
Many traditional MDM product vendors such as IBM, InfoR provide platforms to implement EMPI.
Few organizations have also started using NoSQL and other Big Data platforms for creating a customer hub as explained here.
Hospitals have various departmental systems such as lab systems, radiology systems, EMR systems and other Health Information systems that operate in isolation. Typically patient data is spread out across these disparate systems and it is challenging to have a 360-degree view of the patient.
Hence, hospitals create an EMPI hub that assigns a unique ID to each patient. EMPI systems use algorithms to match and link records across disparate systems. The algorithms also identify duplicate records and reduce the number of false negatives. The typical attributes used by the matching algorithms are first name, last name, DOB, sex, social security number, address and more. The matching algorithms (deterministic, probabilistic/fuzzy) must consider typos, misspellings, transpositions, aliases, etc.
Besides the internal attributes, many organizations also source data from external third parties (e.g. Equifax) that can be used for increasing the accuracy of the matching engine. This is helpful as people change addresses, phone numbers, etc. with time.
Many traditional MDM product vendors such as IBM, InfoR provide platforms to implement EMPI.
Few organizations have also started using NoSQL and other Big Data platforms for creating a customer hub as explained here.
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