Patient Matching on FHIR
Adam Culbertson, Innovator in Residence on Patient Matching, HIMSS
Patient matching: Comparing data from multiple sources using attributes to identify common records. ie. John Smith is the same John Smith.
Patient Matching in probabilistic matching creates a confidence score.
Data + Algorithms = Linked Data.
email is increasingly used.
Metrics for Algorithm Performance
Lack of transparency in how matching algorithms perform
Varied claims
Need beter transparency
Need reporting on Match rates
There are good metrics.
Precision / Recall
- Are two things the same thing?
Possibilities are:
True Positive
True Negative
False Negative
False Positive
Blocking is the process of selecting matches on a particular field before a more detailed comparison is done on the full record.
FHIR is a great solution for Structure
FHIR Enabled Matching
FHIR can be used to create Synthetic data that can be tuned to specific use cases.
FHIR Search Parameters can be used to Create matching queries.
Potential to create a FHIR Extension.
Creating a Test Harness offers opportunities to build a tool to assess best matching tool for a particular use case.
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