helix.personmatching
Project description
helix.personmatching
Entrypoint
helix_personmatching/matchers/matcher.py
Inputs
This code takes in:
- A source Patient/Person resource or a Bundle of Patient/Person resources
- A target Patient/Person resource or a Bundle of Patient/Person resources
- A set of rule options/weights
- Whether to return only successful matches or all match results
- (Optional) Matching threshold (between 0 and 1). Can also be set as an environment variable:
PERSON_MATCH_THRESHOLD
- (Optional) Average score boost (between 0 and 1). Can also be set as an environment variable:
PERSON_MATCH_AVERAGE_SCORE_BOOST
Outputs
- A list of match results where id_source is id of source record and id_target is id of matched record.
Logic
- The code runs through each rule and calculates a uniqueness probability (between 0 and 1) if the rule matches.
- The code then picks the rule with the highest uniqueness probability and uses that probability
- The code then calculates the average of all the other rule probabilities and boosts the uniqueness probability by it.
- The code then sees if any other boosting rules were requested and boosts the probability by those
Weights
There are five cases when matching fields of two records in a rule and the weights that are applied for each case:
- Field present in both sides and match ->
exact_match
- Field present in both sides and partial match ->
partial_match
- Field missing in both sides ->
missing
- Field missing in one side ->
missing
- Field present in both sides but do not match -> 0.0
For boosting rules, there is an additional boost
weight.
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