The diagnostic report generated by the AI system from the patient's input observation.

The human oversight assessment recording the clinician's review and validation of the AI-generated diagnostic report.

The audit trail entry recording the AI system's generation of the diagnostic report.

The communication informing the patient about the AI's involvement in generating the diagnostic report and its subsequent human review.

The AI system that generates the diagnostic report from the patient's clinical findings.

The conformity declaration document for the AI device used in this diagnostic report scenario.

The clinical finding used as input to the AI system when generating the diagnostic report.

The model card describing the AI system's performance, training data, and privacy characteristics.

The diagnostic center that owns and operates the AI system used to generate the diagnostic report.

The patient who is the subject of the AI-generated diagnostic report.

The clinician who performs human oversight and validates the AI-generated diagnostic report.

The role held by the practitioner when reviewing AI-generated diagnostic reports at the organization.

The provenance record describing how and under what legal basis the AI-generated diagnostic report was produced.

Synthetic AI-generated high-risk output derived from NEWS2-inspired input parameters.

Synthetic AI-generated high-risk output derived from NEWS2-inspired input parameters.

Synthetic AI-generated low-risk output derived from NEWS2-inspired input parameters.

Synthetic AI-generated low-risk output derived from NEWS2-inspired input parameters.

Synthetic human oversight assessment documenting the clinician's review of the AI output.

Synthetic human oversight assessment documenting the clinician's review of the AI output.

Synthetic human oversight assessment documenting the clinician's review of the AI output.

Synthetic audit event documenting the AI execution for PoC traceability.

Synthetic audit event documenting the AI execution for PoC traceability.

Synthetic audit event documenting the AI execution for PoC traceability.

Synthetic audit event documenting the AI execution for PoC traceability.

Synthetic patient-facing explanation about AI-supported processing and human review.

Human-corrected clinical result preserving traceability to the original AI-generated output.

Synthetic AI system for NEWS2-inspired early-warning risk assessment.

Synthetic encounter for suspected infection and early-warning risk assessment.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

Synthetic NEWS2-inspired input parameter.

The fictional manufacturer/provider of the RiskAssist AI system.

Synthetic model card for the deterministic AI-output simulation component used in the PoC.

The fictional healthcare organization operating the AI system.

A fictional female patient used in the NEWS2-inspired PoC scenarios.

The fictional clinician responsible for reviewing the AI-generated output.

Synthetic practitioner role representing a trained internal medicine reviewer.

Synthetic provenance resource linking the AI output to the AI system, input data, and legal processing context.

Synthetic provenance resource linking the AI output to the AI system, input data, and legal processing context.

Synthetic provenance resource linking the AI output to the AI system, input data, and legal processing context.

Synthetic provenance resource linking the AI output to the AI system, input data, and legal processing context.

Example showing EHDS secondary use purpose and data permit.

A DocumentReference profile representing technical documentation about an AI system, such as intended use, limitations, risk-related information, performance-related information, and model documentation.

A resource-independent profile indicating that an AI system was involved in generating, reporting, assisting with, or asserting the content of a FHIR resource.

This profile is intended as a common validation and documentation pattern across different FHIR resource types.

An AuditEvent profile documenting execution-related metadata of an AI-supported processing event to support retrospective reconstruction and auditability.

An Observation profile representing a clinical output generated by an AI system, including AI-related transparency metadata and links to the relevant patient, encounter, and AI system.

An ArtifactAssessment profile documenting professional review of an AI-generated output, including whether the result was accepted, corrected, modified, or overridden.

A Communication profile documenting that an explanation regarding an AI-supported clinical decision was provided to a patient. The explanation may describe the role of the AI system, the related human oversight, and the key elements of the resulting clinical decision in accordance with Article 86 of the Trust AI Act.

A PractitionerRole profile representing the role, qualification context, specialty, and AI-related training information of the human reviewer involved in oversight of an AI-supported workflow.

A Provenance profile linking an AI-generated output to the contributing AI system, source data, and relevant processing or governance context.

An Organization profile representing an organization involved in manufacturing, providing, deploying, or operating an AI system, including relevant accountability and contact information.

A Device profile representing an AI system or software component, including system identification, versioning, intended purpose, and selected regulatory documentation metadata.

Records the documented validation status of the AI system, such as clinically validated, under clinical validation, technically validated only, or not clinically validated.

Documents quantitative performance measures and optional disclosures concerning bias, subgroup performance, or limitations of the evaluation.

Documents the stated retention duration for AI-related data, outputs, logs, or documentation.

Records whether the practitioner acting in the documented role has completed training specific to the relevant AI system.

Documents the origin, relevant EHDS-related classifications, applicable permit identifiers, secondary-use purposes, and reported quality characteristics of data used to train or develop the AI system.

Indicates whether the documented AI-supported processing resulted in a decision made solely by automated means.

Records the clinical indication or case-specific reason for applying the AI system in the documented patient context.

Records the identifier of an EHDS data permit associated with the documented secondary use, where applicable.

The EU declaration of conformity shall identify the high-risk AI system.

References the model card that documents the AI system's intended purpose, limitations, performance, risks, and other relevant technical information.

This flag represents whether the patient has been informed about the AI-related processing activity

Records the documented purpose for secondary use of electronic health data in the EHDS context.

Documents whether use of the AI system involves a transfer of personal data to a third country or an international organisation and identifies the destination country or countries where applicable.

Privacy risk management, GDPR accountability

Provides a digital signature and associated metadata to support verification of the integrity and origin of the AI execution audit record.

Classifies the documented use of electronic health data as primary use or secondary use in the EHDS context.

Categories of electronic health data that may be documented for secondary-use and AI-development contexts.

Legal bases listed in Article 6(1) GDPR for documenting the asserted lawful basis for processing personal data.

Selected Article 9(2) GDPR conditions relevant to processing health data and other special categories of personal data in this implementation guide.

Purpose categories used to document the secondary use of electronic health data under the EHDS.

Roles of entities involved in an AI execution audit event.

Clinical purposes for applying an AI system in an individual care context.

Clinical validation statuses applicable to an AI system and its documented intended use.

Assessed data-quality characteristics relevant to AI-system development, validation, testing, or evaluation.

Human oversight actions that may be documented in relation to an AI-generated output or recommendation.

Codes used to classify how an AI system contributed to the content of a FHIR resource.

Performance characteristics that may be documented for an AI system.

Categories distinguishing primary and secondary use of electronic health data in the EHDS context.

Codes representing categories of electronic health data that may be made available for secondary use under the EHDS.

Codes representing the legal bases listed in Article 6(1) GDPR for processing personal data.

Codes representing selected conditions in Article 9(2) GDPR under which special categories of personal data may be processed.

Codes representing permitted categories of purpose for the secondary use of electronic health data under the EHDS.

Codes identifying AI-related documentation artifacts represented by this implementation guide.

Roles used to distinguish entities involved in an AI execution audit event.

Codes describing the clinical purpose for which an AI system was applied in an individual case.

Codes indicating the documented clinical validation status of an AI system for its intended clinical use.

Codes identifying organizational contact responsibilities relevant to data protection and AI-system governance.

Codes describing assessed data-quality characteristics relevant to the development, validation, testing, or evaluation of an AI system.

Codes describing actions taken by a human reviewer in response to an AI-generated output or recommendation.

Codes identifying regulatory identifier types associated with an AI system.

Codes indicating the manner in which an AI system contributed to the content represented by a FHIR resource.

Codes identifying performance characteristics used to document the evaluation of an AI system.

Codes identifying structured properties used to describe regulatory and operational characteristics of an AI system in Device.property.

Codes distinguishing primary use from secondary use of electronic health data in the context of the European Health Data Space.