Healthcare Phi Compliance

作者 affaan-mef648e01899b无许可证275K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库3天前更新

保護医療情報(PHI)コンプライアンス、HIPAA準拠、およびデータセキュリティ。

仅含说明Security
AI 生成的概览

提供医疗 PHI/PII 保护模式,涵盖数据分类、行级安全、审计追踪与泄露防范。

功能
该技能为医疗应用中的患者、临床人员和财务数据保护提供指导模式,适用于 HIPAA、DISHA 和 GDPR。它涵盖三个层面:PHI 与 PII 的数据分类、通过行级安全策略实现的访问控制,以及对每次访问或修改的审计追踪。它还列出常见泄露途径,如错误消息、控制台输出、URL 参数、浏览器存储和服务角色密钥,并提供部署前检查清单和模式标记示例。
适用场景
适用于构建涉及患者记录的功能、设计医疗数据库模式,或为临床系统实现访问控制、身份验证和审计日志时。也适合用于数据暴露的代码审查以及医疗应用中的多租户隔离设置。
运行要求
无需脚本或工具,仅为说明和参考模式。示例涉及 SQL 行级安全和 TypeScript,熟悉这些会有帮助,但无需安装或访问任何内容。

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

sql
ALTER TABLE patients ENABLE ROW LEVEL SECURITY;
-- Scope access by facilityCREATE 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:

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 };  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:

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';

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

typescript
// BAD — leaks PHI in errorthrow new Error(`Patient ${patient.name} not found in ${patient.facility}`);
// GOOD — generic error, details logged server-side with opaque IDs onlylogger.error('Patient lookup failed', { recordId: patient.id, facilityId });throw new Error('Record not found');

Example 2: RLS Policy for Multi-Facility Isolation

sql
-- Doctor at Facility A cannot see Facility B patientsCREATE 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

typescript
// BAD — logs identifiable patient dataconsole.log('Processing patient:', patient);
// GOOD — logs only opaque internal record IDconsole.log('Processing record:', patient.id);// Note: even patient.id should be an opaque UUID, not a medical record number

来源与署名

来源:affaan-m/ecc位于docs/ja-JP/skills/healthcare-phi-compliance提交ef648e0

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