Short answer: Patient matching is deciding whether two records describe the same person. A master patient index (MPI) is the system that keeps one identity per person across the systems of an organisation or region and links their local records. Matching uses identifiers (such as a national health number) when they exist, and otherwise demographics such as name, date of birth, sex and address.
Deterministic and probabilistic
- Deterministic matching requires exact agreement on chosen fields, for example national ID, or name + date of birth + postcode. It is predictable but misses records with typos or changed names.
- Probabilistic matching weighs each field by how much it tells (a rare surname weighs more than a common one) and produces a score; above a threshold records are linked, in a grey zone they go to a person for review.
Both produce two kinds of error: two people merged into one record (dangerous) and one person split into two (data missing). Systems tune thresholds to keep the first very low.
FHIR and matching
FHIR defines a Patient/$match operation: the client sends a Patient resource and the server returns candidates with a match score and grade (certain, probable, possible). National identifiers in Patient.identifier, with a proper system URL, make matching far more reliable.
In Anpheros
In Anpheros the patient keeps their own record and decides what to share, so data from several clinics comes together in one place without a matching step across organisations. Anpheros Platform does not offer $match. When a clinic connects, access is granted by the patient to their own record. Developers: integrating clinic systems with FHIR.
Related pages
Sources
Frequently asked questions
What is a master patient index?
A system that keeps one identity per person and links their records across systems.
What is probabilistic patient matching?
Matching that scores how likely two records are the same person, weighting each field, with a review zone for uncertain cases.
What does FHIR $match do?
It returns candidate Patient records for a given set of demographics, each with a match score.
Why are duplicates dangerous?
Because data may be missing from a record a doctor relies on, or, worse, two people's data may be mixed.
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