Best for
- Implementing drug interaction checking
- Building dose validation engines
- Implementing clinical scoring systems (NEWS2, qSOFA, APACHE, GCS)
affaan-m/ECC/skills/healthcare-cdss-patterns/SKILL.md
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.
Decision brief
Patterns for building Clinical Decision Support Systems that integrate into EMR workflows. CDSS modules are patient safety critical — zero tolerance for false negatives.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/affaan-m/ECC --skill "skills/healthcare-cdss-patterns"Inspect the Agent Skill "healthcare-cdss-patterns" from https://github.com/affaan-m/ECC/blob/d8409a4b0813771235555e32e3d8046a73988bfa/skills/healthcare-cdss-patterns/SKILL.md at commit d8409a4b0813771235555e32e3d8046a73988bfa. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Implementing drug interaction checking
The CDSS engine is a pure function library with zero side effects. Input clinical data, output alerts. This makes it fully testable.
Interaction pairs must be bidirectional: if Drug A interacts with Drug B, then Drug B interacts with Drug A.
Review the “Dose Validation” section in the pinned source before continuing.
Scoring tables must match the Royal College of Physicians specification exactly.
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 93/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 242,963 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
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:
checkInteractions(newDrug, currentMeds, allergies) — Checks a new drug against current medications and known allergies. Returns severity-sorted InteractionAlert[]. Uses DrugInteractionPair data model.validateDose(drug, dose, route, weight, age, renalFunction) — Validates a prescribed dose against weight-based, age-adjusted, and renal-adjusted rules. Returns DoseValidationResult.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: number; supplementalOxygen: boolean;
temperature: number; systolicBP: number; heartRate: number;
consciousness: 'alert' | 'voice' | 'pain' | 'unresponsive';
}
interface NEWS2Result {
total: number; // 0-20
risk: 'low' | 'low-medium' | 'medium' | 'high';
components: Record<string, number>;
escalation: string;
}
Scoring tables must match the Royal College of Physicians specification exactly.
| Severity | UI Behavior | Clinician Action Required |
|---|---|---|
| Critical | Block action. Non-dismissable modal. Red. | Must document override reason to proceed |
| Major | Warning banner inline. Orange. | Must acknowledge before proceeding |
| Minor | Info note inline. Yellow. | Awareness only, no action required |
Critical alerts must NEVER be auto-dismissed or implemented as toast notifications. Override reasons must be stored in the audit trail.
describe('CDSS — Patient Safety', () => {
INTERACTION_PAIRS.forEach(({ drugA, drugB, severity }) => {
it(`detects ${drugA} + ${drugB} (${severity})`, () => {
const alerts = checkInteractions(drugA, [drugB], []);
expect(alerts.length).toBeGreaterThan(0);
expect(alerts[0].severity).toBe(severity);
});
it(`detects ${drugB} + ${drugA} (reverse)`, () => {
const alerts = checkInteractions(drugB, [drugA], []);
expect(alerts.length).toBeGreaterThan(0);
});
});
it('blocks mg/kg drug when weight is missing', () => {
const result = validateDose('gentamicin', 300, 'iv');
expect(result.valid).toBe(false);
expect(result.factors).toContain('weight_missing');
});
it('handles malformed drug data gracefully', () => {
expect(() => checkInteractions('', [], [])).not.toThrow();
});
});
Pass criteria: 100%. A single missed interaction is a patient safety event.
any types for drug or clinical dataconst alerts = checkInteractions('warfarin', ['aspirin', 'metformin'], ['penicillin']);
// [{ severity: 'critical', pair: ['warfarin', 'aspirin'],
// message: 'Increased bleeding risk', recommendation: 'Avoid combination' }]
const ok = validateDose('paracetamol', 1000, 'oral', 70, 45);
// { valid: true, suggestedRange: { min: 500, max: 4000, unit: 'mg' } }
const bad = validateDose('paracetamol', 5000, 'oral', 70, 45);
// { valid: false, message: 'Exceeds absolute max 4000mg' }
const noWeight = validateDose('gentamicin', 300, 'iv');
// { valid: false, factors: ['weight_missing'] }
const result = calculateNEWS2({
respiratoryRate: 24, oxygenSaturation: 93, supplementalOxygen: true,
temperature: 38.5, systolicBP: 100, heartRate: 110, consciousness: 'voice'
});
// { total: 13, risk: 'high', escalation: 'Urgent clinical review. Consider ICU.' }
Frequently asked questions
Patterns for building Clinical Decision Support Systems that integrate into EMR workflows. CDSS modules are patient safety critical — zero tolerance for false negatives.
The source record exposes this install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/healthcare-cdss-patterns". Inspect the command and pinned source before running it.
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