Find duplicates: $match
Use $match operation to find potential duplicate records with configurable query parameters and scoring.
To use the $match operation, you need to set up an MDM module. Read the MDM manual to learn how to run and use it.
The $match operation is used to find potential duplicate records.
It performs a probabilistic search based on a matching model that compares the record you provide with other records in the system across multiple features and estimates how similar they are. The structure of the matching model and its parameters are described on the Matching Model Explanation page.
The result is a list of potential duplicates, each with a calculated match score and a detailed breakdown of feature similarity.
Below we use Patient as an example, but the same flow works for any resource type your matching model targets.
This page provides key information about using $match. For full API details, refer to our Swagger documentation
.
$match
The match operation can be initiated either through the MDM user interface or by using the API.
The $match operation supports several query parameters that let you control how matching is performed and how results are returned:
| Name | Type | Default | Description | Example |
|---|---|---|---|---|
model | string | model | Matching model ID to be used for matching | model |
threshold | integer | 0 | Minimum score threshold for a candidate to appear in the match results | 0 |
page | integer | 1 | Page number of results | 1 |
size | integer | 10 | Number of results per page | 10 |
To call the $match operation, you have to send a FHIR Parameters resource that includes the record for which you want to search potential duplicates. Typically, this record contains identifying data such as:
- Name (given and family)
- Address (e.g., city, state)
- Birth date
- Other identifying attributes if available (e.g., telecom, identifiers)
For example, the request can look like this (Patient example):
POST /fhir/Patient/$match?model=model&threshold=10&page=1&size=10
Content-Type: application/json
{
"resourceType": "Parameters",
"parameter": [
{
"name": "resource",
"resource": {
"name": [
{
"given": [
"Freya"
],
"family": "Shah"
}
],
"address": [
{
"city": "London"
}
],
"birthDate": "1970-12-17"
}
}
]
}
As a result, you will receive the following:
- A list of candidate duplicate records
- For each candidate record:
match_weight— an overall similarity score calculated by the matching modelmatch_details— per-feature similarity contributions (e.g., name similarity, date of birth match, address closeness, etc.)resource— the full FHIR resource for that candidate
The response is sorted by match_weight in descending order so that the most similar records appear first.
For example:
[
{
"match_details": {
"fn": 13.336495228175629,
"dob": 10.59415069916466,
"ext": -10.517360697819983,
"sex": 0
},
"match_weight": 13.413285229520307,
"resource": {
"id": "236",
"resourceType": "Patient",
"name": [
{
"given": [
"Freya"
],
"family": "Shah"
}
],
"address": [
{
"city": "Londodn"
}
],
"birthDate": "1970-12-17",
"identifier": [
{
"value": "62",
"system": "cluster"
}
]
}
},
{
"match_details": {
"fn": 13.336495228175629,
"dob": 10.59415069916466,
"ext": -10.517360697819983,
"sex": 0
},
"match_weight": 13.413285229520307,
"resource": {
"id": "242",
"resourceType": "Patient",
"name": [
{
"given": [
"Freya"
],
"family": "Shah"
}
],
"address": [
{
"city": "Lonnod"
}
],
"birthDate": "1970-12-17",
"identifier": [
{
"value": "62",
"system": "cluster"
}
]
}
},
{
"match_details": {
"fn": 13.104401641242227,
"dob": 10.59415069916466,
"ext": -10.517360697819983,
"sex": 0
},
"match_weight": 13.181191642586905,
"resource": {
"id": "238",
"resourceType": "Patient",
"name": [
{
"given": [
"Shah"
],
"family": "Freya"
}
],
"address": [
{
"city": "London"
}
],
"telecom": [
{
"value": "f.s@flynn.com",
"system": "email"
}
],
"birthDate": "1970-12-17",
"identifier": [
{
"value": "62",
"system": "cluster"
}
]
}
}
]
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