Clinical Safety Statement

• Templates guide clinicians through structured data collection using SNOMED CT coded clinical findings, observations and procedures
• Templates may include conditional logic to display relevant fields based on clinical context
• Observation items support standardised units of measurement and derived calculations

• Clinical templates are version-controlled with automatically incrementing version numbers
• When a consultation is created, the complete template state is captured as an immutable snapshot
• Historical consultations always display the exact template configuration from when they were recorded
• Subsequent template modifications do not alter existing consultation records

This approach supports medico-legal defensibility and ensures the clinical record reflects what was documented at the time of care.

• Validated clinical questionnaires such as PHQ-9, GAD-7 and condition-specific assessments use automated scoring based on published methodologies
• Derived scores are calculated only when all required questions are answered, preventing incomplete or misleading results
• Questionnaire responses are mapped to SNOMED CT codes for integration into the clinical record

• Certain responses, such as indicators of self-harm risk, can be flagged for clinical attention
• Red flag identification supports appropriate triage and escalation workflows

• Questionnaire responses undergo validation before being written to the clinical record
• Clinicians retain responsibility for interpreting questionnaire results within the broader clinical context

• Medication safety alerts for potential drug allergies, drug-drug interactions and contraindications based on documented patient conditions
• Immunisation safety checks including pregnancy, immunosuppression, anaphylaxis history, age eligibility and required dose intervals
• Ingredient-level and drug family allergy matching to identify potential cross-reactivity

• Hard alerts require documented clinical justification before proceeding
• Soft alerts present warnings for clinician consideration
• Informational alerts provide educational context without blocking workflow

Clinical Decision Support within Jump EHR operates using transparent, deterministic rules rather than adaptive or self-learning algorithms.

• Alerts are generated based on coded clinical data such as documented allergies, diagnoses, medications, questionnaire responses and structured observations
• Rules are derived from established clinical logic, configuration settings and clinician-authored content
• The system does not independently infer diagnoses or generate probabilistic risk predictions
• CDS behaviour does not change dynamically based on population learning or model training

This ensures alerting is predictable, auditable and dependent on the completeness and accuracy of the clinical data entered.

• CDS rules depend on accurate and complete patient records
• Missing or incorrectly coded information may result in missed alerts
• CDS is a support tool and does not replace clinical judgement or knowledge of the individual patient
• Clinicians must review all alerts and make independent clinical decisions

• When a clinician proceeds despite a hard alert, they must document their clinical rationale
• Override justifications are recorded in the audit trail for governance and review