Agent skill

Healthcare Cdss Patterns

by affaan-m in affaan-m/ECC

Clinical Decision Support System (CDSS) development patterns.

MITAuto-check passedResearch & Science

Install Healthcare Cdss Patterns

skills CLI
$ npx skills add affaan-m/ECC --skill healthcare-cdss-patterns -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC healthcare-cdss-patterns --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/healthcare-cdss-patterns .claude/skills/healthcare-cdss-patterns && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
healthcare-cdss-patterns
GitHub stars
277k
Used in
1 other repo
Token cost
~2.4k tokens
SKILL.md length
343 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Clinical Decision Support System (CDSS) development patterns.

  • Works in 3 steps: checkInteractions(newDrug, currentMeds,… → validateDose(drug, dose, route, weight,… → calculateNEWS2(vitals) — National Early…
  • Building clinical decision support — drug interaction checks
  • SKILL.md covers When to Use, How It Works and Examples
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Healthcare Cdss Patterns is an agent skill from affaan-m/ECC. 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.

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Clinical and healthcare research. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • Building clinical decision support — drug interaction checks
  • Dose validation
  • Clinical scoring

Example prompts

  • “/healthcare-cdss-patterns”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. checkInteractions(newDrug, currentMeds, allergies) — Checks a new drug against current medications and known allergies. Returns…
  2. validateDose(drug, dose, route, weight, age, renalFunction) — Validates a prescribed dose against weight-based, age-adjusted, and…
  3. calculateNEWS2(vitals) — National Early Warning Score 2 from NEWS2Input. Returns NEWS2Result with total score, risk level, and escalation…

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Healthcare Cdss Patterns loads about 2.4k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 343 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~89
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 343 words, ~2,355 tokens.

Download SKILL.mdSave it as .claude/skills/healthcare-cdss-patterns/SKILL.md (or your agent's skills folder).
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
metadata.origin
Health1 Super Speciality Hospitals — contributed by Dr. Keyur Patel

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.' }

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/healthcare-cdss-patterns of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Healthcare Cdss Patterns next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Healthcare Cdss Patterns compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Healthcare Cdss Patterns this skillaffaan-m/ECC277k1 repos~2.4kAutomated safety check: PassMIT
Clinical Trials Databasegoogle-deepmind/science-skills3.2k2 repos~3.2kAutomated safety check: PassApache-2.0
CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw6171 repos~1.8kAutomated safety check: PassNone
Biomedical Analysis Dispatchxjtulyc/MedgeClaw6171 repos~2kAutomated safety check: PassNone
Research Paperluwill/research-skills862—~1.9kAutomated safety check: PassNone
Research Proposalluwill/research-skills862—~4.5kAutomated safety check: NotesNone

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Questions about Healthcare Cdss Patterns

What does Healthcare Cdss Patterns do?

Clinical Decision Support System (CDSS) development patterns. Healthcare Cdss Patterns is an agent skill from affaan-m/ECC. Clinical Decision Support System (CDSS) development patterns.

When should I use Healthcare Cdss Patterns?

Healthcare Cdss Patterns fits situations like: building clinical decision support — drug interaction checks; dose validation; clinical scoring.

How do I install Healthcare Cdss Patterns in Claude Code?

Run `npx skills add affaan-m/ECC --skill healthcare-cdss-patterns -a claude-code`. Or copy the skill folder (skills/healthcare-cdss-patterns in affaan-m/ECC) into .claude/skills/healthcare-cdss-patterns in your project. Claude Code loads it when a task matches its description.

How do I install Healthcare Cdss Patterns in Codex?

Run `npx skills add affaan-m/ECC --skill healthcare-cdss-patterns -a codex`. Or copy the skill folder (skills/healthcare-cdss-patterns in affaan-m/ECC) into .agents/skills/healthcare-cdss-patterns in your project. Codex loads it when a task matches its description.

Can I use Healthcare Cdss Patterns in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill healthcare-cdss-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/healthcare-cdss-patterns, .gemini/skills/healthcare-cdss-patterns, .github/skills/healthcare-cdss-patterns and .opencode/skills/healthcare-cdss-patterns in your project.

What does Healthcare Cdss Patterns need to run?

SKILL.md names no scripts, command-line tools or credentials: Healthcare Cdss Patterns is instructions for the agent only.

Does Healthcare Cdss Patterns access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Healthcare Cdss Patterns safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Healthcare Cdss Patterns use?

Healthcare Cdss Patterns is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Healthcare Cdss Patterns use?

About 2.4k tokens (SKILL.md is roughly 9.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Healthcare Cdss Patterns?

Skills that share tags, products or a category with Healthcare Cdss Patterns: Clinical Trials Database (google-deepmind/science-skills, 3.2k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars) and Research Paper (luwill/research-skills, 862 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Healthcare Cdss Patterns?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.