FHIR Prediction Model: Data Structure for Risk Assessment
HS.FHIR.DTL.vR4.Model.Element.RiskAssessment.prediction - InterSystems Documentation InterSystems Documentation HS.FHIR.
Summary
InterSystems has published a data structure designed to predict outcomes related to diseases or conditions. This structure incorporates probabilistic information and temporal constraints, aiding advanced risk assessment in clinical settings.
Details
This document is a technical reference detailing the 'RiskAssessment.prediction' class based on FHIR (Fast Healthcare Interoperability Resources) specifications. This class provides the data structure used for predicting outcomes regarding specific diseases or conditions. Key properties include 'outcome' (a CodeableConcept indicating possible results), 'probabilityDecimal' (the probability of occurrence), and 'qualitativeRisk' (a qualitative risk assessment). Furthermore, it defines elements such as 'rationale' (explanation of prediction) and temporal constraints like 'whenPeriod' and 'whenRange'. This structure enables the integration of dynamic risk information—such as 'how likely' or 'when' something might occur—beyond simple diagnostic data. As AI and machine learning-driven prognostic models are adopted in Japanese healthcare, this serves as a crucial foundation for structuring such complex clinical data via FHIR standards, ensuring interoperability between different Electronic Health Record (EHR) systems. Technically, the class inherits from BackboneElement, detailing specifications for XML data exchange and property management. This allows prediction model outputs to be handled in a standardized format, contributing to the enhancement of medical information system linkage.
Technology Note
FHIR（Fast Healthcare Interoperability Resources）は医療データ交換の国際標準。このエントリの関連技術: FHIR
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