feat: add healthcare domain skills and agent

New skills:
- healthcare-emr-patterns: EMR/EHR encounter workflows, smart templates, medication safety, clinical UI patterns
- healthcare-phi-compliance: PHI/PII protection patterns, RLS templates, leak vector checklist, audit trail patterns
- healthcare-cdss-patterns: Drug interaction checking, dose validation, clinical scoring (NEWS2/qSOFA), alert severity
- healthcare-eval-harness: Patient safety CI/CD gate — CDSS accuracy, PHI exposure, data integrity, clinical workflows

New agent:
- healthcare-reviewer: Clinical safety reviewer for CDSS accuracy, PHI compliance, medical data integrity

All patterns are generalized and framework-agnostic. Applicable to any health-tech stack.
Origin: Health1 Super Speciality Hospitals, Ahmedabad, India.
This commit is contained in:
Dr. Keyur Patel
2026-03-27 03:17:49 +00:00
parent 678fb6f0d3
commit 63737544a1
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---
name: healthcare-reviewer
description: Reviews healthcare application code for clinical safety, CDSS accuracy, PHI compliance, and medical data integrity. Specialized for EMR/EHR, clinical decision support, and health information systems.
tools: ["Read", "Grep", "Glob"]
model: opus
---
# Healthcare Reviewer — Clinical Safety & PHI Compliance
You are a clinical informatics reviewer for healthcare software. Patient safety is your top priority. You review code for clinical accuracy, data protection, and regulatory compliance.
## Your Responsibilities
1. **CDSS accuracy** — Verify drug interaction logic, dose validation rules, and clinical scoring implementations match published medical standards
2. **PHI/PII protection** — Scan for patient data exposure in logs, errors, responses, URLs, and client storage
3. **Clinical data integrity** — Ensure audit trails, locked records, and cascade protection
4. **Medical data correctness** — Verify ICD-10/SNOMED mappings, lab reference ranges, and drug database entries
5. **Integration compliance** — Validate HL7/FHIR message handling and error recovery
## Critical Checks
### CDSS Engine
- [ ] All drug interaction pairs produce correct alerts (both directions)
- [ ] Dose validation rules fire on out-of-range values
- [ ] Clinical scoring matches published specification (NEWS2 = Royal College of Physicians, qSOFA = Sepsis-3)
- [ ] No false negatives (missed interaction = patient safety event)
- [ ] Malformed inputs produce errors, NOT silent passes
### PHI Protection
- [ ] No patient data in `console.log`, `console.error`, or error messages
- [ ] No PHI in URL parameters or query strings
- [ ] No PHI in browser localStorage/sessionStorage
- [ ] No `service_role` key in client-side code
- [ ] RLS enabled on all tables with patient data
- [ ] Cross-facility data isolation verified
### Clinical Workflow
- [ ] Encounter lock prevents edits (addendum only)
- [ ] Audit trail entry on every create/read/update/delete of clinical data
- [ ] Critical alerts are non-dismissable (not toast notifications)
- [ ] Override reasons logged when clinician proceeds past critical alert
- [ ] Red flag symptoms trigger visible alerts
### Data Integrity
- [ ] No CASCADE DELETE on patient records
- [ ] Concurrent edit detection (optimistic locking or conflict resolution)
- [ ] No orphaned records across clinical tables
- [ ] Timestamps use consistent timezone
## Output Format
```
## Healthcare Review: [module/feature]
### Patient Safety Impact: [CRITICAL / HIGH / MEDIUM / LOW / NONE]
### Clinical Accuracy
- CDSS: [checks passed/failed]
- Drug DB: [verified/issues]
- Scoring: [matches spec/deviates]
### PHI Compliance
- Exposure vectors checked: [list]
- Issues found: [list or none]
### Issues
1. [PATIENT SAFETY / CLINICAL / PHI / TECHNICAL] Description
- Impact: [potential harm or exposure]
- Fix: [required change]
### Verdict: [SAFE TO DEPLOY / NEEDS FIXES / BLOCK — PATIENT SAFETY RISK]
```
## Rules
- When in doubt about clinical accuracy, flag as NEEDS REVIEW — never approve uncertain clinical logic
- A single missed drug interaction is worse than a hundred false alarms
- PHI exposure is always CRITICAL severity, regardless of how small the leak
- Never approve code that silently catches CDSS errors

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---
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"
observe: "PostToolUse"
feedback: "manual"
rollback: "git revert"
---
# 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 Activate
- 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
## Architecture
```
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)
```
**Key principle:** The CDSS engine should be a pure function library with zero side effects. Input clinical data, output alerts. This makes it fully testable.
## Drug Interaction Checking
### Data Model
```typescript
interface DrugInteractionPair {
drugA: string; // generic name
drugB: string; // generic name
severity: 'critical' | 'major' | 'minor';
mechanism: string; // e.g., "CYP3A4 inhibition"
clinicalEffect: string; // e.g., "Increased bleeding risk"
recommendation: string; // e.g., "Avoid combination" or "Monitor INR closely"
}
interface InteractionAlert {
severity: 'critical' | 'major' | 'minor';
pair: [string, string];
message: string;
recommendation: string;
}
```
### Implementation Pattern
```typescript
function checkInteractions(
newDrug: string,
currentMedications: string[],
allergyList: string[]
): InteractionAlert[] {
const alerts: InteractionAlert[] = [];
// Check drug-drug interactions
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
});
}
}
// Check drug-allergy interactions
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'
});
}
}
// Sort by severity (critical first)
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. Store once, check both directions.
## Dose Validation
```typescript
interface DoseValidationResult {
valid: boolean;
message: string;
suggestedRange: { min: number; max: number; unit: string };
factors: string[]; // what was considered (weight, age, renal function)
}
function validateDose(
drug: string,
dose: number,
route: 'oral' | 'iv' | 'im' | 'sc' | 'topical',
patientWeight?: number,
patientAge?: number,
renalFunction?: number // eGFR
): DoseValidationResult {
const rules = getDoseRules(drug, route);
if (!rules) return { valid: true, message: 'No validation rules available', suggestedRange: null, factors: [] };
// Weight-based dosing
if (rules.weightBased && patientWeight) {
const maxDose = rules.maxPerKg * patientWeight;
if (dose > maxDose) {
return {
valid: false,
message: `Dose ${dose}${rules.unit} exceeds max ${maxDose}${rules.unit} for ${patientWeight}kg patient`,
suggestedRange: { min: rules.minPerKg * patientWeight, max: maxDose, unit: rules.unit },
factors: ['weight']
};
}
}
// Absolute max dose
if (dose > rules.absoluteMax) {
return {
valid: false,
message: `Dose ${dose}${rules.unit} exceeds absolute max ${rules.absoluteMax}${rules.unit}`,
suggestedRange: { min: rules.typicalMin, max: rules.absoluteMax, unit: rules.unit },
factors: ['absolute_max']
};
}
return { valid: true, message: 'Within range', suggestedRange: { min: rules.typicalMin, max: rules.typicalMax, unit: rules.unit }, factors: [] };
}
```
## Clinical Scoring: NEWS2
National Early Warning Score 2 — standardized assessment of acute illness severity:
```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; // recommended clinical action
}
```
Scoring tables must match the Royal College of Physicians NEWS2 specification exactly. Any deviation is a patient safety issue.
## 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 |
**Rules:**
- Critical alerts must NEVER be auto-dismissed
- Critical alerts must NEVER be toast notifications
- Override reasons must be stored in the audit trail
- Alert fatigue is real — only use critical for genuinely dangerous situations
## Testing CDSS (Zero Tolerance for False Negatives)
```typescript
describe('CDSS — Patient Safety', () => {
// Every known interaction pair MUST fire
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);
});
// Bidirectional check
it(`detects ${drugB} + ${drugA} (reverse)`, () => {
const alerts = checkInteractions(drugB, [drugA], []);
expect(alerts.length).toBeGreaterThan(0);
});
});
// Dose validation
DOSE_RULES.forEach((rule) => {
it(`validates ${rule.drug}: ${rule.scenario}`, () => {
const result = validateDose(rule.drug, rule.dose, rule.route, rule.weight, rule.age);
expect(result.valid).toBe(rule.expectedValid);
});
});
// No silent failures
it('handles malformed drug data gracefully', () => {
expect(() => checkInteractions('', [], [])).not.toThrow();
expect(() => checkInteractions(null as any, [], [])).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
- ❌ Testing with mocked data only (must test with real drug names)
- ❌ Silently catching errors in CDSS engine (must surface failures loudly)

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---
name: healthcare-emr-patterns
description: EMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry.
origin: Health1 Super Speciality Hospitals — contributed by Dr. Keyur Patel
version: "1.0.0"
observe: "PostToolUse"
feedback: "manual"
rollback: "git revert"
---
# Healthcare EMR Development Patterns
Patterns for building Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems. Prioritizes patient safety, clinical accuracy, and practitioner efficiency.
## When to Activate
- Building patient encounter workflows (complaint → exam → diagnosis → prescription)
- Implementing clinical note-taking (structured + free text + voice-to-text)
- Designing prescription/medication modules with drug interaction checking
- Integrating Clinical Decision Support Systems (CDSS)
- Building lab result displays with reference range highlighting
- Implementing audit trails for clinical data
- Designing healthcare-accessible UIs for clinical data entry
## Core Principles
### 1. Patient Safety First
Every design decision must be evaluated against: "Could this harm a patient?"
- Drug interactions MUST alert, not silently pass
- Abnormal lab values MUST be visually flagged
- Critical vitals MUST trigger escalation workflows
- No clinical data modification without audit trail
### 2. Single-Page Encounter Flow
Clinical encounters should flow vertically on a single page — no tab switching during patient interaction:
```
Patient Header (sticky — always visible)
├── Demographics, allergies, active medications
Encounter Flow (vertical scroll)
├── 1. Chief Complaint (structured templates + free text)
├── 2. History of Present Illness
├── 3. Physical Examination (system-wise)
├── 4. Vitals (auto-trigger clinical scoring)
├── 5. Diagnosis (ICD-10/SNOMED search)
├── 6. Medications (drug DB + interaction check)
├── 7. Investigations (lab/radiology orders)
├── 8. Plan & Follow-up
└── 9. Sign / Lock / Print
```
### 3. Smart Template System
Build templates for common presentations:
```typescript
interface ClinicalTemplate {
id: string;
name: string; // e.g., "Chest Pain"
chips: string[]; // clickable symptom chips
requiredFields: string[]; // mandatory data points
redFlags: string[]; // triggers non-dismissable alert
icdSuggestions: string[]; // pre-mapped diagnosis codes
}
```
**Red flags** in any template must trigger a visible, non-dismissable alert — NOT a toast notification.
### 4. Medication Safety Pattern
```
User selects drug
→ Check current medications for interactions
→ Check encounter medications for interactions
→ Check patient allergies
→ Validate dose against weight/age/renal function
→ Display alerts (critical = block, major = require override reason)
→ Log override reason if clinician proceeds
```
Critical interactions should **block prescribing by default**. The clinician must explicitly override with a documented reason.
### 5. Locked Encounter Pattern
Once a clinical encounter is signed:
- No edits allowed — only addendum
- Addendum is a new record linked to the original
- Both original and addendum appear in the patient timeline
- Audit trail captures who signed, when, and any addenda
## UI Patterns for Clinical Data
### Vitals Display
- Current values with normal range highlighting (green/yellow/red)
- Trend arrows comparing to previous measurement
- Clinical scoring auto-calculated (NEWS2, qSOFA, MEWS)
- Scoring result displayed inline with escalation guidance
### Lab Results Display
- Normal range highlighting with institution-specific ranges
- Previous value comparison (trend)
- Critical values flagged with non-dismissable alert
- Timestamp of collection and analysis
- Pending orders shown with expected turnaround
### Prescription PDF
- One-click generation
- Patient demographics, allergies, diagnosis
- Drug name (generic + brand), dose, route, frequency, duration
- Clinician signature block
- QR code linking to digital record (optional)
## Accessibility for Healthcare
Healthcare UIs have stricter accessibility requirements than typical web apps:
- **4.5:1 minimum contrast** (WCAG AA) — clinicians work in varied lighting
- **Large touch targets** (44x44px minimum) — for gloved/rushed interaction
- **Keyboard navigation** — for power users entering data rapidly
- **No color-only indicators** — always pair color with text/icon (colorblind clinicians)
- **Screen reader labels** on all form fields — for voice-assisted data entry
- **No auto-dismissing toasts** for clinical alerts — clinician must actively acknowledge
## Anti-Patterns
- ❌ Storing clinical data in browser localStorage
- ❌ Silent failures in drug interaction checking
- ❌ Dismissable toasts for critical clinical alerts
- ❌ Tab-based encounter UIs that fragment the clinical workflow
- ❌ Allowing edits to signed/locked encounters
- ❌ Displaying clinical data without audit trail
- ❌ Using `any` type for clinical data structures

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---
name: healthcare-eval-harness
description: Patient safety evaluation harness for healthcare application deployments. Automated test suites for CDSS accuracy, PHI exposure, clinical workflow integrity, and integration compliance. Blocks deployments on safety failures.
origin: Health1 Super Speciality Hospitals — contributed by Dr. Keyur Patel
version: "1.0.0"
observe: "PostToolUse"
feedback: "manual"
rollback: "git revert"
---
# Healthcare Eval Harness — Patient Safety Verification
Automated verification system for healthcare application deployments. A single CRITICAL failure blocks deployment. Patient safety is non-negotiable.
## When to Activate
- Before any deployment of EMR/EHR applications
- After modifying CDSS logic (drug interactions, dose validation, scoring)
- After changing database schemas that touch patient data
- After modifying authentication or access control
- During CI/CD pipeline configuration for healthcare apps
- After resolving merge conflicts in clinical modules
## Eval Categories
### 1. CDSS Accuracy (CRITICAL — 100% required)
Tests all clinical decision support logic:
- Drug interaction pairs: every known pair must fire an alert
- Dose validation: out-of-range doses must be flagged
- Clinical scoring: results must match published specifications
- No false negatives: a missed alert is a patient safety event
- No silent failures: malformed input must error, not silently pass
```bash
npx jest --testPathPattern='tests/cdss' --bail --ci
```
### 2. PHI Exposure (CRITICAL — 100% required)
Tests for protected health information leaks:
- API error responses contain no PHI
- Console output contains no patient data
- URL parameters contain no PHI
- Browser storage contains no PHI
- Cross-facility data isolation works (multi-tenant)
- Unauthenticated requests return zero patient rows
- Service role keys absent from client bundles
```bash
npx jest --testPathPattern='tests/security/phi' --bail --ci
```
### 3. Data Integrity (CRITICAL — 100% required)
Tests for clinical data safety:
- Locked encounters cannot be modified
- Audit trail entries exist for every write operation
- Cascade deletes are blocked on patient records
- Concurrent edits trigger conflict resolution
- No orphaned records across related tables
```bash
npx jest --testPathPattern='tests/data-integrity' --bail --ci
```
### 4. Clinical Workflow (HIGH — 95%+ required)
Tests end-to-end clinical workflows:
- Complete encounter flow (complaint → exam → diagnosis → Rx → lock)
- Template rendering and submission for all clinical templates
- Medication set population and interaction checking
- Drug/diagnosis search functionality
- Prescription PDF generation
- Red flag alert triggering
```bash
npx jest --testPathPattern='tests/clinical' --ci
```
### 5. Integration Compliance (HIGH — 95%+ required)
Tests external system integrations:
- HL7 message parsing (v2.x)
- FHIR resource validation (if applicable)
- Lab result mapping to correct patients
- Malformed message handling (no crashes)
```bash
npx jest --testPathPattern='tests/integration' --ci
```
## CI/CD Integration
### GitHub Actions Example
```yaml
name: Healthcare Safety Gate
on: [push, pull_request]
jobs:
safety-gate:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '20'
- run: npm ci
# CRITICAL gates — must pass 100%
- name: CDSS Accuracy
run: npx jest --testPathPattern='tests/cdss' --bail --ci
- name: PHI Exposure Check
run: npx jest --testPathPattern='tests/security/phi' --bail --ci
- name: Data Integrity
run: npx jest --testPathPattern='tests/data-integrity' --bail --ci
# HIGH gates — must pass 95%+
- name: Clinical Workflows
run: npx jest --testPathPattern='tests/clinical' --ci
- name: Integration Compliance
run: npx jest --testPathPattern='tests/integration' --ci
```
## Pass/Fail Matrix
| Category | Threshold | On Failure |
|----------|-----------|------------|
| CDSS Accuracy | 100% | **BLOCK deployment** |
| PHI Exposure | 100% | **BLOCK deployment** |
| Data Integrity | 100% | **BLOCK deployment** |
| Clinical Workflow | 95%+ | WARN, allow with review |
| Integration | 95%+ | WARN, allow with review |
## Eval Report Format
```
## Healthcare Eval: [date] [commit]
### Patient Safety: PASS / FAIL
| Category | Tests | Pass | Fail | Status |
|----------|-------|------|------|--------|
| CDSS Accuracy | N | N | 0 | PASS |
| PHI Exposure | N | N | 0 | PASS |
| Data Integrity | N | N | 0 | PASS |
| Clinical Workflow | N | N | N | 95%+ |
| Integration | N | N | N | 95%+ |
### Coverage: X% (target: 80%+)
### Verdict: SAFE TO DEPLOY / BLOCKED
```
## Anti-Patterns
- ❌ Skipping CDSS tests "because they passed last time"
- ❌ Setting CRITICAL thresholds below 100%
- ❌ Using `--no-bail` on CRITICAL test suites
- ❌ Mocking the CDSS engine in integration tests (must test real logic)
- ❌ Allowing deployments when safety gate is red

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---
name: healthcare-phi-compliance
description: Protected Health Information (PHI) and Personally Identifiable Information (PII) compliance patterns for healthcare applications. Covers data classification, access control, audit trails, encryption, and common leak vectors.
origin: Health1 Super Speciality Hospitals — contributed by Dr. Keyur Patel
version: "1.0.0"
observe: "PostToolUse"
feedback: "manual"
rollback: "git revert"
---
# Healthcare PHI/PII Compliance Patterns
Patterns for protecting patient data, clinician data, and financial data in healthcare applications. Applicable to HIPAA (US), DISHA (India), GDPR (EU), and general healthcare data protection.
## When to Activate
- Building any feature that touches patient records
- Implementing access control or authentication for clinical systems
- Designing database schemas for healthcare data
- Building APIs that return patient or clinician data
- Implementing audit trails or logging
- Reviewing code for data exposure vulnerabilities
- Setting up Row-Level Security (RLS) for multi-tenant healthcare systems
## Data Classification
### PHI (Protected Health Information)
Any data that can identify a patient AND relates to their health:
- Patient name, date of birth, address, phone, email
- National ID numbers (SSN, Aadhaar, NHS number)
- Medical record numbers
- Diagnoses, medications, lab results, imaging
- Insurance policy and claim details
- Appointment and admission records
- Any combination of the above
### PII (Personally Identifiable Information)
Non-patient sensitive data in healthcare systems:
- Clinician/staff personal details
- Doctor fee structures and payout amounts
- Employee salary and bank details
- Vendor payment information
## Access Control Patterns
### Row-Level Security (Supabase/PostgreSQL)
```sql
-- Enable RLS on every PHI table
ALTER TABLE patients ENABLE ROW LEVEL SECURITY;
-- Scope access by facility/centre
CREATE POLICY "staff_read_own_facility"
ON patients FOR SELECT
TO authenticated
USING (
facility_id IN (
SELECT facility_id FROM staff_assignments
WHERE user_id = auth.uid()
AND role IN ('doctor', 'nurse', 'lab_tech', 'admin')
)
);
-- Audit log: insert-only (no updates, no deletes)
CREATE POLICY "audit_insert_only"
ON audit_log FOR INSERT
TO authenticated
WITH CHECK (user_id = auth.uid());
CREATE POLICY "audit_no_modify" ON audit_log FOR UPDATE USING (false);
CREATE POLICY "audit_no_delete" ON audit_log FOR DELETE USING (false);
```
### API Authentication
- Every API route handling PHI MUST require authentication
- Use short-lived tokens (JWT with 15-min expiry for clinical sessions)
- Implement session timeout (auto-logout after inactivity)
- Log every PHI access with user ID, timestamp, and resource accessed
## Common Leak Vectors (Check Every Deployment)
### 1. Error Messages
```typescript
// ❌ BAD — leaks PHI in error
throw new Error(`Patient ${patient.name} not found in ${patient.facility}`);
// ✅ GOOD — generic error, log details server-side
logger.error('Patient lookup failed', { patientId, facilityId });
throw new Error('Record not found');
```
### 2. Console Output
```typescript
// ❌ BAD
console.log('Processing patient:', patient);
// ✅ GOOD
console.log('Processing patient:', patient.id); // ID only
```
### 3. URL Parameters
```
❌ /patients?name=John+Doe&dob=1990-01-01
✅ /patients/uuid-here (lookup by opaque ID)
```
### 4. Browser Storage
```typescript
// ❌ NEVER store PHI in localStorage/sessionStorage
localStorage.setItem('currentPatient', JSON.stringify(patient));
// ✅ Keep PHI in memory only, fetch on demand
const [patient, setPatient] = useState<Patient | null>(null);
```
### 5. Service Role Keys
```typescript
// ❌ NEVER use service_role key in client-side code
const supabase = createClient(url, SUPABASE_SERVICE_ROLE_KEY);
// ✅ ALWAYS use anon key — let RLS enforce access
const supabase = createClient(url, SUPABASE_ANON_KEY);
```
### 6. Logs and Monitoring
- Never log full patient records
- Log patient IDs, not names
- Sanitize stack traces before sending to error tracking services
- Ensure log storage itself is access-controlled
## Audit Trail Requirements
Every PHI access or modification must be logged:
```typescript
interface AuditEntry {
timestamp: string;
user_id: string;
patient_id: string;
action: 'create' | 'read' | 'update' | 'delete' | 'print' | 'export';
resource_type: string;
resource_id: string;
changes?: { before: object; after: object }; // for updates
ip_address: string;
session_id: string;
}
```
## Database Schema Tagging
Mark PHI/PII columns at the schema level so automated tools can identify them:
```sql
COMMENT ON COLUMN patients.name IS 'PHI: patient_name';
COMMENT ON COLUMN patients.dob IS 'PHI: date_of_birth';
COMMENT ON COLUMN patients.aadhaar IS 'PHI: national_id';
COMMENT ON COLUMN doctor_payouts.amount IS 'PII: financial';
COMMENT ON COLUMN employees.salary IS 'PII: financial';
```
## Deployment Checklist
Before every deployment of a healthcare application:
- [ ] No PHI in error messages or stack traces
- [ ] No PHI in console.log/console.error
- [ ] No PHI in URL parameters
- [ ] No PHI in browser storage
- [ ] No service_role key in client code
- [ ] RLS enabled on all PHI/PII tables
- [ ] Audit trail for all data modifications
- [ ] Session timeout configured
- [ ] API authentication on all PHI endpoints
- [ ] Cross-facility data isolation verified