healthcare-cdss-patterns

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.
origin	Health1 Super Speciality Hospitals — contributed by Dr. Keyur Patel
version	1.0.0

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

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) {
     ((newDrug, allergy)) {
      alerts.({ : , : [newDrug, allergy],
        : ,
        :  });
    }
  }
   alerts.( (a.) - (b.));
}

Interaction pairs must be bidirectional: if Drug A interacts with Drug B, then Drug B interacts with Drug A.

Dose Validation

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) {
     (!patientWeight || patientWeight <= ) {
       { : , : ,
        : , : [] };
    }
    factors.();
     maxDose = rules. * patientWeight;
     (dose > maxDose) {
       { : , : ,
        : { : rules. * patientWeight, : maxDose, : rules. }, factors };
    }
  }

  
   (rules. && patientAge !== ) {
    factors.();
     ageMax = rules.(patientAge);
     (dose > ageMax) {
       { : , : ,
        : { : rules., : ageMax, : rules. }, factors };
    }
  }

  
   (rules. && renalFunction !== ) {
    factors.();
     renalMax = rules.(renalFunction);
     (dose > renalMax) {
       { : , : ,
        : { : rules., : renalMax, : rules. }, factors };
    }
  }

  
   (dose > rules.) {
     { : , : ,
      : { : rules., : rules., : rules. },
      : [...factors, ] };
  }
   { : , : ,
    : { : rules., : rules., : rules. }, factors };
}

Clinical Scoring: NEWS2

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

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.

Testing CDSS (Zero Tolerance for False Negatives)

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();
  });
  (,  {
    ( (, [], []))..();
  });
});

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

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

Example 2: Dose Validation

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

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.' }