FHIR and MPI Challenges: Advanced Patient Matching Techniques Based on US Core Profile
Finding the Full Meaning of FHIR Revealed Through Its Widespread Adoption in Healthcare Today
Summary
This article analyzes the practical data processing challenges for implementing a Master Patient Index (MPI) based on the FHIR US Core Patient profile. It emphasizes that advanced matching techniques, such as handling identifiers and addresses, are necessary beyond mere standard compliance to ensure effective implementation.
Details
While the FHIR US Core Patient profile provides a foundational framework for healthcare data exchange, it is insufficient on its own for building an effective Master Patient Index (MPI). This article focuses on advanced matching techniques required in real-world operations. Specifically, it advises that identifiers (SSN/MRN) are the highest signal source, followed by name, and then telecom. It also provides a regulatory perspective, suggesting that race and ethnicity should be used as 'blocking factors' to narrow candidate lists, rather than being scored directly in matching algorithms. Furthermore, address data must be treated not as a single point-in-time record, but as multi-faceted signals with defined periods (period.start/end). For elements like names and birth dates, implementing fuzzy matching (e.g., Damerau-Levenshtein) is crucial to handle typos or variations in format. Understanding and implementing these technical challenges is key to realizing a truly functional MPI.
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