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Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks,
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Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks,
name: healthcare-cdss-patterns description: Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks, dose validation, clinical scoring, or alert severity. metadata: version: "1.0.0" origin: Health1 Super Speciality Hospitals — contributed by Dr. Keyur Patel
Patterns for building Clinical Decision Support Systems that integrate into EMR workflows. CDSS modules are patient safety critical — zero tolerance for false negatives.
The CDSS engine is a **pure function library with zero side effects**. Input clinical data, output alerts. This makes it fully testable.
Three primary modules:
1. **`checkInteractions(newDrug, currentMeds, allergies)`** — Checks a new drug against current medications and known allergies. Returns severity-sorted `InteractionAlert[]`. Uses `DrugInteractionPair` data model. 2. **`validateDose(drug, dose, route, weight, age, renalFunction)`** — Validates a prescribed dose against weight-based, age-adjusted, and renal-adjusted rules. Returns `DoseValidationResult`. 3. **`calculateNEWS2(vitals)`** — National Early Warning Score 2 from `NEWS2Input`. Returns `NEWS2Result` with total score, risk level, and escalation guidance.
EMR UI ↓ (user enters data) CDSS Engine (pure functions, no side effects) ├── Drug Interaction Checker ├── Dose Validator ├── Clinical Scoring (NEWS2, qSOFA, etc.) └── Alert Classifier ↓ (returns alerts) EMR UI (displays alerts inline, blocks if critical)
interface DrugInteractionPair {
drugA: string; // generic name
drugB: string; // generic name
severity: 'critical' | 'major' | 'minor';
mechanism: string;
clinicalEffect: string;
recommendation: string;
}
function checkInteractions(
newDrug: string,
currentMedications: string[],
allergyList: string[]
): InteractionAlert[] {
if (!newDrug) return [];
const alerts: InteractionAlert[] = [];
for (const current of currentMedications) {
const interaction = findInteraction(newDrug, current);
if (interaction) {
alerts.push({ severity: interaction.severity, pair: [newDrug, current],
message: interaction.clinicalEffect, recommendation: interaction.recommendation });
}
}
for (const allergy of allergyList) {
if (isCrossReactive(newDrug, allergy)) {
alerts.push({ severity: 'critical', pair: [newDrug, allergy],
message: `Cross-reactivity with documented allergy: ${allergy}`,
recommendation: 'Do not prescribe without allergy consultation' });
}
}
return alerts.sort((a, b) => severityOrder(a.severity) - severityOrder(b.severity));
}Interaction pairs must be **bidirectional**: if Drug A interacts with Drug B, then Drug B interacts with Drug A.
interface DoseValidationResult {
valid: boolean;
message: string;
suggestedRange: { min: number; max: number; unit: string } | null;
factors: string[];
}
function validateDose(
drug: string,
dose: number,
route: 'oral' | 'iv' | 'im' | 'sc' | 'topical',
patientWeight?: number,
patientAge?: number,
renalFunction?: number
): DoseValidationResult {
const rules = getDoseRules(drug, route);
if (!rules) return { valid: true, message: 'No validation rules available', suggestedRange: null, factors: [] };
const factors: string[] = [];
// SAFETY: if rules require weight but weight missing, BLOCK (not pass)
if (rules.weightBased) {
if (!patientWeight || patientWeight <= 0) {
return { valid: false, message: `Weight required for ${drug} (mg/kg drug)`,
suggestedRange: null, factors: ['weight_missing'] };
}
factors.push('weight');
const maxDose = rules.maxPerKg * patientWeight;
if (dose > maxDose) {
return { valid: false, message: `Dose exceeds max for ${patientWeight}kg`,
suggestedRange: { min: rules.minPerKg * patientWeight, max: maxDose, unit: rules.unit }, factors };
}
}
// Age-based adjustment (when rules define age brackets and age is provided)
if (rules.ageAdjusted && patientAge !== undefined) {
factors.push('age');
const ageMax = rules.getAgeAdjustedMax(patientAge);
if (dose > ageMax) {
return { valid: false, message: `Exceeds age-adjusted max for ${patientAge}yr`,
suggestedRange: { min: rules.typicalMin, max: ageMax, unit: rules.unit }, factors };
}
}
// Renal adjustment (when rules define eGFR brackets and eGFR is provided)
if (rules.renalAdjusted && renalFunction !== undefined) {
factors.push('renal');
const renalMax = rules.getRenalAdjustedMax(renalFunction);
if (dose > renalMax) {
return { valid: false, message: `Exceeds renal-adjusted max for eGFR ${renalFunction}`,
suggestedRange: { min: rules.typicalMin, max: renalMax, unit: rules.unit }, factors };
}
}
// Absolute max
if (dose > rules.absoluteMax) {
return { valid: false, message: `Exceeds absolute max ${rules.absoluteMax}${rules.unit}`,
suggestedRange: { min: rules.typicalMin, max: rules.absoluteMax, unit: rules.unit },
factors: [...factors, 'absolute_max'] };
}
return { valid: true, message: 'Within range',
suggestedRange: { min: rules.typicalMin, max: rules.typicalMax, unit: rules.unit }, factors };
}interface NEWS2Input {
respiratoryRate: number; oxygenSaturation: nYour agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills
Repo: affaan-m/ECC
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