Autonomous Patient Record Linking Across Distributed Healthcare Entities
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Solution Overview
Problem
Current systems for linking patient information records across different healthcare providers are inefficient, as they require a common patient identifier and manual review of uncertain matches, which is costly and prone to errors, especially in complex cases like recurring cancer patients where comprehensive medical history is crucial.
Innovation Solution
A system where each healthcare entity uses its own patient identification algorithm to link patient information records, allowing autonomous decision-making on matching criteria and policies, with the option for local storage and periodic updating of links, reducing data communication and storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a common patient identifier and centralized EMPI system are used to link patient records across different healthcare entities, then patient data can be retrieved and linked across distributed sources, but the system complexity increases and manual review of uncertain matches is required which is costly and time-consuming
Solution Approach 1:
The patent divides the centralized EMPI system into distributed patient identification algorithms at each healthcare entity. Each entity independently maintains and executes its own matching algorithm locally, eliminating the need for a complex centralized system while achieving the same record linkage function across distributed sources.
Solution Approach 2:
Each healthcare entity autonomously performs patient record matching using its own identification algorithm without requiring centralized coordination. The system enables self-service record linkage where entities independently resolve uncertain matches without manual review, reducing operational costs and time requirements.
2Reliability
If manual review is performed for uncertain matches to minimize linkage errors, then patient safety is improved, but the cost and time required for record linkage increases significantly
Solution Approach 1:
The patent implements preliminary confidence assessment in the patient identification algorithm that pre-evaluates match quality before requiring manual review. By incorporating confidence scoring and uncertainty quantification into the automated matching process, the system identifies high-confidence matches that require no manual review, reserving human review only for edge cases.
Solution Approach 2:
The system incorporates feedback mechanisms where match results and confidence scores are continuously refined based on outcome validation. This feedback loop improves the accuracy of automated matching over time, progressively reducing the volume of records requiring manual review while maintaining or improving linkage accuracy.
3Loss of energy
If centralized data storage and periodic updating is implemented, then data communication needs are reduced, but the challenge of maintaining data freshness and accessibility across distributed entities arises
Solution Approach 1:
The patent enables each healthcare entity to maintain local copies of patient identification data and matching algorithms tailored to its specific needs and data characteristics. This local quality approach allows entities to optimize their matching processes independently while periodically synchronizing with other entities, reducing communication overhead while maintaining data relevance and freshness locally.
Data Source
AI summary
A system for linking corresponding patient information records is disclosed. A plurality of entities (1,1a) have respective patient databases comprising patient information records (3, 3a). Each entity (1, 1a) has associated therewith a patient identification algorithm (4,4a) for matching corresponding patient information records (3, 3a) of the same patient at different entities (1,1a). A linking subsystem (6) maintains a set of links (7) of a first entity (1) of the plurality of entities (1,1a). The linking subsystem (6) is arranged for linking patient information records (3) of the first entity (1) with corresponding patient information records (3a) of the other entities (1a). A link (ID, RID, RLoc) is established when a given patient information record (3) of the first entity (1) matches a corresponding patient information record (3a) of another entity (1a) based on the patient identification algorithm (4) of the first entity (1). The links provide an association between locally-assigned patient identifiers (ID, RID) of the same patient at different entities (1,1a).