Healthcare Cdss Patterns

by affaan-mef648e01899bNo license275K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 3 days ago

臨床意思決定支援システム(CDSS)パターン、医学的推論、およびエビデンスベースの実装。

AI-generated overview

Implementation patterns for building clinical decision support modules such as drug interaction checks, dose validation and NEWS2 scoring.

What it does
Provides development patterns for clinical decision support systems that plug into EMR workflows. It defines TypeScript interfaces and pure functions for drug interaction checking, dose validation with weight, age and renal adjustments, and NEWS2 clinical scoring, plus alert severity rules and UI behavior. It also gives testing criteria and anti-patterns, with the stated goal of zero false negatives.
When to use it
Use when implementing or reviewing CDSS features such as drug interaction checking, dose validation engines, clinical scoring systems, or alert handling in medication order entry. It suits teams integrating safety checks into an EMR and needing interface and test guidance. It is not a clinical reference or a dataset analysis tool.
Requirements
No scripts or bundled assets; instructions only. The patterns assume a TypeScript/JavaScript environment with a test runner such as Jest, plus drug interaction and dose rule data sources. No credentials or network access are specified.

Healthcare CDSS Development Patterns

Patterns for building Clinical Decision Support Systems that integrate into EMR workflows. CDSS modules are patient safety critical — zero tolerance for false negatives.

When to Use

  • Implementing drug interaction checking
  • Building dose validation engines
  • Implementing clinical scoring systems (NEWS2, qSOFA, APACHE, GCS)
  • Designing alert systems for abnormal clinical values
  • Building medication order entry with safety checks
  • Integrating lab result interpretation with clinical context

How It Works

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)

Drug Interaction Checking

typescript
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.

Dose Validation

typescript
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 };}

Clinical Scoring: NEWS2

typescript
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.

Alert Severity and UI Behavior

SeverityUI BehaviorClinician Action Required
CriticalBlock action. Non-dismissable modal. Red.Must document override reason to proceed
MajorWarning banner inline. Orange.Must acknowledge before proceeding
MinorInfo 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.

Testing CDSS (Zero Tolerance for False Negatives)

typescript
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.

Anti-Patterns

  • Making CDSS checks optional or skippable without documented reason
  • Implementing interaction checks as toast notifications
  • Using any types for drug or clinical data
  • Hardcoding interaction pairs instead of using a maintainable data structure
  • Silently catching errors in CDSS engine (must surface failures loudly)
  • Skipping weight-based validation when weight is not available (must block, not pass)

Examples

Example 1: Drug Interaction Check

typescript
const alerts = checkInteractions('warfarin', ['aspirin', 'metformin'], ['penicillin']);// [{ severity: 'critical', pair: ['warfarin', 'aspirin'],//    message: 'Increased bleeding risk', recommendation: 'Avoid combination' }]

Example 2: Dose Validation

typescript
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'] }

Example 3: NEWS2 Scoring

typescript
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.' }

Source and attribution

Source:affaan-m/eccindocs/ja-JP/skills/healthcare-cdss-patternsat commitef648e0

License: No license

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