Healthcare Cdss Patterns

affaan-m/ECC/skills/healthcare-cdss-patterns

作者 affaan-mef648e01899ba3e8dc6371642deaaf64b4477775無授權條款275K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫4 天前更新

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.

AI 產生的概覽

建構臨床決策支援模組的模式:藥物交互作用檢查、劑量驗證、臨床評分與警示嚴重度分級。

功能
提供接入 EMR 工作流程的臨床決策支援模組開發模式與 TypeScript 範例。內容涵蓋藥物交互作用檢查、結合體重、年齡與腎功能的劑量驗證、NEWS2 與 qSOFA 等臨床評分,以及警示嚴重度分級與對應的介面行為。文件也說明病人安全關鍵程式碼的測試要求與反模式。
適用情境
適用於在 EMR 中實作或審查臨床決策支援功能時,例如藥物交互作用檢查、劑量驗證引擎、臨床評分系統或警示處理。適合需要參考模式與安全規則而非可直接執行函式庫的開發者。
執行需求
不需要指令碼或執行階段相依項目,僅為說明性文件。範例假定使用 TypeScript 或 JavaScript 環境,藥物交互作用資料、劑量規則與評分表由使用者自行提供。

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.' }

來源與署名

來源:affaan-m/ECC位於skills/healthcare-cdss-patterns提交ef648e0

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