Field mapping explorer

Provenance information, including Author Time Stamp and Author Organization, where relevant. These concepts do not substitute for model-inference or audit-recording times.

AuditEvent.occurredPeriod can represent the execution interval, while AuditEvent.recorded records when the audit event was logged. AuditEvent.source.observer can identify the reporting source. MedLog-specific invocation identifiers, protocol version, parent-event linkage, and other workflow context can remain in the linked MedLog payload or defined extensions.

OpenTelemetry log Timestamp and ObservedTimestamp can distinguish source-event and collection times. Populate trace and span identifiers only when genuine tracing context exists; use gen_ai.conversation.id only when the MedLog run identifier has the same conversation or thread scope.

No direct counterpart for the complete AI-specific configuration of a model invocation.

A software model can be represented by a Device. Device.identifier can identify the software instance, while Device.version.value can record its software version. Model-card references, training-data versions, deployment identifiers, test-time modifications, and other invocation-specific configuration can remain in the linked MedLog payload or associated documentation.

Preserve richer model metadata under medlog.model_instance.*. For generative AI, gen_ai.request.model can identify the requested model and gen_ai.response.model the responding model when independently known. These attributes do not replace model-version, deployment, or other configuration metadata.

Provenance Author, Author Role, and Author Organization; Care Team Members and facility information where applicable. Authorship and initiation of a model invocation are distinct concepts.

AuditEvent.agent can represent actors involved in the event. AuditEvent.agent.who.identifier can preserve a native account identifier and namespace, while AuditEvent.agent.role can record the active security role. References to Practitioner or PractitionerRole can add human, clinical-role, and organizational context. Session or login context not represented directly can remain in MedLog.

Preserve the full provenance chain in medlog.user_identity.*. Compatible application context can additionally use user.id, user.name, and session.id. These attributes do not replace identifier namespaces, caller ordering, or other MedLog-specific provenance information.

Patient Identifier and encounter or appointment information where applicable.

AuditEvent.patient can identify a patient whose data were involved in the event, and AuditEvent.encounter can provide encounter context. AuditEvent.entity.what can reference other relevant target or contextual resources, such as an Appointment. When provenance of a generated or updated FHIR resource is being described, Provenance.target identifies that resource.

Preserve target type, identifier namespace, and clinical references in medlog.target_identity.*. Do not populate user.id merely because the target is a patient; being the subject of a prediction does not establish participation as an application user.

Laboratory, Vital Signs, Medications, Problems, Clinical Notes, Diagnostic Imaging, and other clinical data used by the model.

Inputs can reference resources matching their clinical meaning, including Observation, DocumentReference, Condition, and MedicationRequest. Provenance.entity.what can identify source entities used in producing an output. Input versions, preprocessing state, feature vectors, prompts, or other information needed for reconstruction can remain in MedLog.

Retain inputs or controlled-access references in the structured MedLog payload. For generative AI, compatible chat history can use gen_ai.input.messages, while separately supplied system instructions can use gen_ai.system_instructions. Arbitrary feature vectors or clinical variables should not be relabeled as messages solely to fit Gen AI conventions.

No direct counterpart for AI execution traces, tool calls, retrieval results, attribution maps, or invocation-specific state.

A DocumentReference can reference stored artifacts; for example, DocumentReference.content.attachment.url can point to controlled-access artifact storage. Artifact type, format, version, and linkage to the originating invocation can remain in MedLog or explicitly defined extensions.

Preserve artifact metadata and payloads or references in medlog.artifact.*. Compatible generative-AI operations can additionally use semantic conventions such as gen_ai.tool.name and gen_ai.retrieval.documents. Other internal artifacts remain MedLog-specific.

Clinical Notes or other USCDI elements corresponding to the output’s actual clinical meaning; there is no universal AI-output element.

Use resources corresponding to the output’s clinical meaning, such as RiskAssessment for a clinical risk prediction or DocumentReference for a generated document. Provenance.target can identify a resource generated or updated by the activity. The original model output should remain distinguishable from subsequent human edits, transformations, and presentation events.

Preserve outputs in medlog.output.*. For generative AI, corresponding model-response messages can use gen_ai.output.messages. gen_ai.output.type describes the output type requested by the client and should not be treated as an unconditional equivalent of a MedLog output-type field.

Adverse Events, orders, Medications, Problems, Laboratory results, and other elements corresponding to the clinical or operational endpoint being measured.

Outcomes can reference resources matching their clinical meaning, such as ServiceRequest or MedicationRequest for orders, MedicationAdministration for administered therapy, Condition or Observation for clinical endpoints, and Appointment.status for attendance. Linkage between the outcome and originating AI interaction remains explicit in MedLog. AuditEvent.outcome records the success or failure of the audited event and is not itself a clinical outcome.

Preserve endpoint values, times, clinical references, and linkage evidence in medlog.outcome.*. Delayed outcomes can be emitted as later records linked to the originating invocation. Clinical benefit or harm should not be represented as inference execution status, nor should an execution span remain open while awaiting clinical follow-up.

No direct counterpart for AI-specific feedback; clinical assessment data are not automatically equivalent to feedback on an AI interaction.

QuestionnaireResponse can represent feedback collected through a defined questionnaire. Its author, subject, encounter, and questionnaire linkage can provide additional context where applicable. Other ratings or comments can remain in a linked MedLog payload. Preserve the feedback instrument and version, respondent attribution, and explicit linkage to the invocation or output.

Preserve feedback in medlog.feedback.*. Feedback explicitly evaluating a generative-AI response can additionally use gen_ai.evaluation.name together with gen_ai.evaluation.score.value or gen_ai.evaluation.score.label where applicable. General comments should not be converted into an artificial score.