healthcare-phi-compliance
Use when code touches patient PHI or PII in a healthcare system: data classification, Postgres row-level security, tamper-proof audit trails and leak vectors. Applies to HIPAA, GDPR and DISHA; covers error messages, logs and URLs as common leak paths.
- License 许可
- MIT
- 所属仓库
- monoes/monomind
- 最近更新
- 2026-11-14
- Stars
- ★ 23
- Forks
- 2
01 前言 Front Matter
- name
- healthcare-phi-compliance
- tags
- [ "legal", "security", "engineering", "compliance", "postgres" ]
- tools
- []
- source
- https://github.com/affaan-m/ECC
- license
- MIT
- description
- Use when code touches patient PHI or PII in a healthcare system: data classification, Postgres row-level security, tamper-proof audit trails and leak vectors. Applies to HIPAA, GDPR and DISHA; covers error messages, logs and URLs as common leak paths.
- source_path
- skills/healthcare-phi-compliance
- source_commit
- bf70150eb2df8070024e5bdf08e4aa08959e2735
02 资源文件 1
- 许可证LICENSE.txt1.0 KB
03 SKILL.md 正文
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 Use
- 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
How It Works
Healthcare data protection operates on three layers: classification (what is sensitive), access control (who can see it), and audit (who did see it).
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, or any combination of the above.
PII (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: Row-Level Security
ALTER TABLE patients ENABLE ROW LEVEL SECURITY;
-- Scope access by facility
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 (tamper-proof)
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);
Audit Trail
Every PHI access or modification must be logged:
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 };
ip_address: string;
session_id: string;
}
Common Leak Vectors
Error messages: Never include patient-identifying data in error messages thrown to the client. Log details server-side only.
Console output: Never log full patient objects. Use opaque internal record IDs (UUIDs) — not medical record numbers, national IDs, or names.
URL parameters: Never put patient-identifying data in query strings or path segments that could appear in logs or browser history. Use opaque UUIDs only.
Browser storage: Never store PHI in localStorage or sessionStorage. Keep PHI in memory only, fetch on demand.
Service role keys: Never use the service_role key in client-side code. Always use the anon/publishable key and let RLS enforce access.
Logs and monitoring: Never log full patient records. Use opaque record IDs only (not medical record numbers). Sanitize stack traces before sending to error tracking services.
Database Schema Tagging
Mark PHI/PII columns at the schema level:
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';
Deployment Checklist
Before every deployment:
- 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
Examples
Example 1: Safe vs Unsafe Error Handling
// BAD — leaks PHI in error
throw new Error(`Patient ${patient.name} not found in ${patient.facility}`);
// GOOD — generic error, details logged server-side with opaque IDs only
logger.error('Patient lookup failed', { recordId: patient.id, facilityId });
throw new Error('Record not found');
Example 2: RLS Policy for Multi-Facility Isolation
-- Doctor at Facility A cannot see Facility B patients
CREATE POLICY "facility_isolation"
ON patients FOR SELECT TO authenticated
USING (facility_id IN (
SELECT facility_id FROM staff_assignments WHERE user_id = auth.uid()
));
-- Test: login as doctor-facility-a, query facility-b patients
-- Expected: 0 rows returned
Example 3: Safe Logging
// BAD — logs identifiable patient data
console.log('Processing patient:', patient);
// GOOD — logs only opaque internal record ID
console.log('Processing record:', patient.id);
// Note: even patient.id should be an opaque UUID, not a medical record number
04 同仓库更多 Skills
zk-steward
Org role guidance for a ZK steward: engineer zero-knowledge proof systems with circuit design, SNARK vs STARK choice and security review. This is zero-knowledge cryptography, not Zettelkasten note-taking.
writing-plans
Use when you have a spec or requirements for a multi-step coding task and must write an implementation plan before touching code. Produces bite-sized TDD tasks with exact file paths, code and commands for an engineer with zero context.
write-spec
Write a feature spec or PRD from a problem statement or feature idea. Use when turning a vague idea or user request into a structured document, scoping a feature with goals and non-goals, defining success metrics and acceptance criteria, or breaking a big ask into a phased spec.
write-query
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.
workflow-automation
Org role guidance for workflow automation: build and maintain CI/CD definitions in GitHub Actions or equivalent: triggers, jobs, matrices, caching. Covers path filters, dependency caching, parallel jobs, timeouts and fail-fast ordering.
workflow-architect
Org role guidance for a workflow architect: map full workflow trees for systems, user journeys and agents, covering every branch and failure. Covers discovering workflows from code, handoff contracts, timeouts, recovery paths and observable state.