healthcare-cdss-patterns

Clinical decision support in EMR integration applies safety-critical checks like drug interaction validation and clinical scoring. Pure functions ensure deterministic, testable logic with zero side effects, preventing false negatives in patient safety scenarios.

Implement dose validation and drug interaction checks using modular pure functions like checkInteractions and validateDose. These accept patient data and return structured DoseValidationResult and DrugInteractionPair models for deterministic EMR alerting.

Yes, the CDSS pattern library supports clinical scoring including NEWS2, qSOFA, APACHE, and GCS. It defines calculateNEWS2 functions that return NEWS2Result data models, enabling deterministic score computation for EMR escalation workflows.

No, the clinical decision support library has zero external dependencies. It operates as a standalone pure-function library with no side effects, requiring only patient data inputs to execute interaction checks and clinical scoring.

Structure deterministic clinical scoring components as modular pure functions with clear interfaces like calculateNEWS2. Define typed result models such as NEWS2Result and DrugInteractionPair to ensure testable, side-effect-free EMR workflow integration.

Avoid pure-function CDSS patterns when your EMR workflow requires real-time stateful monitoring, ambient event listening, or direct database writes. These patterns focus on deterministic data transformations and return actionable alerts rather than managing persistent clinical state.