clqms-be/docs/audit-logging-plan.md

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# Audit Logging Architecture Plan for CLQMS
> **Clinical Laboratory Quality Management System (CLQMS)** - A comprehensive audit trail strategy for tracking changes across master data, patient records, and laboratory operations.
---
## Executive Summary
This document outlines a unified audit logging architecture for CLQMS, designed to provide complete traceability of data changes while maintaining optimal performance and maintainability. The approach separates audit logs into three domain-specific tables, utilizing JSON for flexible value storage.
---
## 1. Current State Analysis
### Existing Audit Infrastructure
| Aspect | Current Status |
|--------|---------------|
| **Database Tables** | 3 tables exist in migrations (patreglog, patvisitlog, specimenlog) |
| **Implementation** | Tables created but not actively used |
| **Structure** | Fixed column approach (FldName, FldValuePrev) |
| **Code Coverage** | No models or controllers implemented |
| **Application Logging** | Basic CodeIgniter file logging for debug/errors |
### Pain Points Identified
-**3 separate tables** with nearly identical schemas
-**Fixed column structure** - rigid and requires schema changes for new entities
-**No implementation** - audit tables exist but aren't populated
-**Maintenance overhead** - adding new entities requires new migrations
---
## 2. Proposed Architecture
### 2.1 Domain Separation
We categorize audit logs by **data domain** and **access patterns**:
| Table | Domain | Volume | Retention | Use Case |
|-------|--------|--------|-----------|----------|
| `master_audit_log` | Reference Data | Low | Permanent | Organizations, Users, ValueSets |
| `patient_audit_log` | Patient Records | Medium | 7 years | Demographics, Contacts, Insurance |
| `order_audit_log` | Operations | High | 2 years | Orders, Tests, Specimens, Results |
### 2.2 Unified Table Structure
#### Master Audit Log
```sql
CREATE TABLE master_audit_log (
id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
entity_type VARCHAR(50) NOT NULL, -- 'organization', 'user', 'valueset'
entity_id VARCHAR(36) NOT NULL, -- UUID or primary key
action ENUM('CREATE', 'UPDATE', 'DELETE', 'PATCH') NOT NULL,
old_values JSON NULL, -- Complete snapshot before change
new_values JSON NULL, -- Complete snapshot after change
changed_fields JSON, -- Array of modified field names
-- Context
user_id VARCHAR(36),
site_id VARCHAR(36),
ip_address VARCHAR(45),
user_agent VARCHAR(500),
app_version VARCHAR(20),
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
INDEX idx_entity (entity_type, entity_id),
INDEX idx_created (created_at),
INDEX idx_user (user_id, created_at)
) ENGINE=InnoDB;
```
#### Patient Audit Log
```sql
CREATE TABLE patient_audit_log (
id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
entity_type VARCHAR(50) NOT NULL, -- 'patient', 'contact', 'insurance'
entity_id VARCHAR(36) NOT NULL,
patient_id VARCHAR(36), -- Context FK for patient
action ENUM('CREATE', 'UPDATE', 'DELETE', 'MERGE', 'UNMERGE') NOT NULL,
old_values JSON NULL,
new_values JSON NULL,
changed_fields JSON,
reason TEXT, -- Why the change was made
-- Context
user_id VARCHAR(36),
site_id VARCHAR(36),
ip_address VARCHAR(45),
session_id VARCHAR(100),
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
INDEX idx_entity (entity_type, entity_id),
INDEX idx_patient (patient_id, created_at),
INDEX idx_created (created_at),
INDEX idx_user (user_id, created_at)
) ENGINE=InnoDB;
```
#### Order/Test Audit Log
```sql
CREATE TABLE order_audit_log (
id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
entity_type VARCHAR(50) NOT NULL, -- 'order', 'test', 'specimen', 'result'
entity_id VARCHAR(36) NOT NULL,
-- Context FKs
patient_id VARCHAR(36),
visit_id VARCHAR(36),
order_id VARCHAR(36),
action ENUM('CREATE', 'UPDATE', 'DELETE', 'CANCEL', 'REORDER', 'COLLECT', 'RESULT') NOT NULL,
old_values JSON NULL,
new_values JSON NULL,
changed_fields JSON,
status_transition VARCHAR(100), -- e.g., 'pending->collected'
-- Context
user_id VARCHAR(36),
site_id VARCHAR(36),
device_id VARCHAR(36), -- Instrument/edge device
ip_address VARCHAR(45),
session_id VARCHAR(100),
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
INDEX idx_entity (entity_type, entity_id),
INDEX idx_order (order_id, created_at),
INDEX idx_patient (patient_id, created_at),
INDEX idx_created (created_at),
INDEX idx_user (user_id, created_at)
) ENGINE=InnoDB;
```
---
## 3. JSON Value Structure
### Example Audit Entry
```json
{
"id": 15243,
"entity_type": "patient",
"entity_id": "PAT-2026-001234",
"action": "UPDATE",
"old_values": {
"NameFirst": "John",
"NameLast": "Doe",
"Gender": "M",
"BirthDate": "1990-01-15",
"Phone": "+1-555-0100"
},
"new_values": {
"NameFirst": "Johnny",
"NameLast": "Doe-Smith",
"Gender": "M",
"BirthDate": "1990-01-15",
"Phone": "+1-555-0199"
},
"changed_fields": ["NameFirst", "NameLast", "Phone"],
"user_id": "USR-001",
"site_id": "SITE-001",
"created_at": "2026-02-19T14:30:00Z"
}
```
### Benefits of JSON Approach
**Schema Evolution** - Add new fields without migrations
**Complete Snapshots** - Reconstruct full record state at any point
**Flexible Queries** - MySQL 8.0+ supports JSON indexing and extraction
**Audit Integrity** - Store exactly what changed, no data loss
---
## 4. Implementation Strategy
### 4.1 Central Audit Service
```php
<?php
namespace App\Services;
class AuditService
{
/**
* Log an audit event to the appropriate table
*/
public static function log(
string $category, // 'master', 'patient', 'order'
string $entityType, // e.g., 'patient', 'order'
string $entityId,
string $action,
?array $oldValues = null,
?array $newValues = null,
?string $reason = null,
?array $context = null
): void {
$changedFields = self::calculateChangedFields($oldValues, $newValues);
$data = [
'entity_type' => $entityType,
'entity_id' => $entityId,
'action' => $action,
'old_values' => $oldValues ? json_encode($oldValues) : null,
'new_values' => $newValues ? json_encode($newValues) : null,
'changed_fields' => json_encode($changedFields),
'user_id' => auth()->id() ?? 'SYSTEM',
'site_id' => session('site_id') ?? 'MAIN',
'created_at' => date('Y-m-d H:i:s')
];
// Route to appropriate table
$table = match($category) {
'master' => 'master_audit_log',
'patient' => 'patient_audit_log',
'order' => 'order_audit_log',
default => throw new \InvalidArgumentException("Unknown category: $category")
};
// Async logging recommended for high-volume operations
self::dispatchAuditJob($table, $data);
}
private static function calculateChangedFields(?array $old, ?array $new): array
{
if (!$old || !$new) return [];
$changes = [];
$allKeys = array_unique(array_merge(array_keys($old), array_keys($new)));
foreach ($allKeys as $key) {
if (($old[$key] ?? null) !== ($new[$key] ?? null)) {
$changes[] = $key;
}
}
return $changes;
}
}
```
### 4.2 Model Integration
```php
<?php
namespace App\Models;
use App\Services\AuditService;
class PatientModel extends BaseModel
{
protected $table = 'patients';
protected $primaryKey = 'PatientID';
protected function logAudit(
string $action,
?array $oldValues = null,
?array $newValues = null
): void {
AuditService::log(
category: 'patient',
entityType: 'patient',
entityId: $this->getPatientId(),
action: $action,
oldValues: $oldValues,
newValues: $newValues
);
}
// Override save method to auto-log
public function save($data): bool
{
$oldData = $this->find($data['PatientID'] ?? null);
$result = parent::save($data);
if ($result) {
$this->logAudit(
$oldData ? 'UPDATE' : 'CREATE',
$oldData?->toArray(),
$this->find($data['PatientID'])->toArray()
);
}
return $result;
}
}
```
---
## 5. Query Patterns & Performance
### 5.1 Common Queries
```sql
-- View entity history
SELECT * FROM patient_audit_log
WHERE entity_type = 'patient'
AND entity_id = 'PAT-2026-001234'
ORDER BY created_at DESC;
-- User activity report
SELECT entity_type, action, COUNT(*) as count
FROM patient_audit_log
WHERE user_id = 'USR-001'
AND created_at > DATE_SUB(NOW(), INTERVAL 7 DAY)
GROUP BY entity_type, action;
-- Find all changes to a specific field
SELECT * FROM order_audit_log
WHERE JSON_CONTAINS(changed_fields, '"result_value"')
AND patient_id = 'PAT-001'
AND created_at > '2026-01-01';
```
### 5.2 Partitioning Strategy (Order/Test)
For high-volume tables, implement monthly partitioning:
```sql
CREATE TABLE order_audit_log (
-- ... columns
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
) ENGINE=InnoDB
PARTITION BY RANGE (YEAR(created_at) * 100 + MONTH(created_at)) (
PARTITION p202601 VALUES LESS THAN (202602),
PARTITION p202602 VALUES LESS THAN (202603),
PARTITION p_future VALUES LESS THAN MAXVALUE
);
```
---
## 6. Soft Delete Handling
Soft deletes ARE captured as audit entries with complete snapshots:
```php
// When soft deleting a patient:
AuditService::log(
category: 'patient',
entityType: 'patient',
entityId: $patientId,
action: 'DELETE',
oldValues: $fullRecordBeforeDelete, // Complete last known state
newValues: null,
reason: 'Patient requested data removal'
);
```
This ensures:
- ✅ Full audit trail even for deleted records
- ✅ Compliance with "right to be forgotten" (GDPR)
- ✅ Ability to restore accidentally deleted records
---
## 7. Migration Plan
### Phase 1: Foundation (Week 1)
- [ ] Drop existing unused tables (patreglog, patvisitlog, specimenlog)
- [ ] Create new audit tables with JSON columns
- [ ] Create AuditService class
- [ ] Add database indexes
### Phase 2: Core Implementation (Week 2)
- [ ] Integrate AuditService into Patient model
- [ ] Integrate AuditService into Order model
- [ ] Integrate AuditService into Master data models
- [ ] Add audit trail to authentication events
### Phase 3: API & UI (Week 3)
- [ ] Create API endpoints for querying audit logs
- [ ] Build admin interface for audit review
- [ ] Add audit export functionality (CSV/PDF)
### Phase 4: Optimization (Week 4)
- [ ] Implement async logging queue
- [ ] Add table partitioning for order_audit_log
- [ ] Set up retention policies and archiving
- [ ] Performance testing and tuning
---
## 8. Retention & Archiving Strategy
| Table | Retention Period | Archive Action |
|-------|---------------|----------------|
| `master_audit_log` | Permanent | None (keep forever) |
| `patient_audit_log` | 7 years | Move to cold storage after 7 years |
| `order_audit_log` | 2 years | Partition rotation: drop old partitions |
### Automated Maintenance
```sql
-- Monthly job: Archive old patient audit logs
INSERT INTO patient_audit_log_archive
SELECT * FROM patient_audit_log
WHERE created_at < DATE_SUB(NOW(), INTERVAL 7 YEAR);
DELETE FROM patient_audit_log
WHERE created_at < DATE_SUB(NOW(), INTERVAL 7 YEAR);
-- Monthly job: Drop old order partitions
ALTER TABLE order_audit_log DROP PARTITION p202501;
```
---
## 9. Questions for Stakeholders
Before implementation, please confirm:
1. **Retention Policy**: Are the proposed retention periods (master=forever, patient=7 years, order=2 years) compliant with your regulatory requirements?
2. **Async vs Sync**: Should audit logging be synchronous (block on failure) or asynchronous (queue-based)? Recommended: async for order/test operations.
3. **Archive Storage**: Where should archived audit logs be stored? Options: separate database, file storage (S3), or compressed tables.
4. **User Access**: Which user roles need access to audit trails? Should users see their own audit history?
5. **Compliance**: Do you need specific compliance features (e.g., HIPAA audit trail requirements, 21 CFR Part 11 for FDA)?
---
## 10. Key Design Decisions Summary
| Decision | Choice | Rationale |
|----------|--------|-----------|
| **Table Count** | 3 tables | Separates concerns, optimizes queries, different retention |
| **JSON vs Columns** | JSON for values | Flexible, handles schema changes, complete snapshots |
| **Full vs Diff** | Full snapshots | Easier to reconstruct history, no data loss |
| **Soft Deletes** | Captured in audit | Compliance and restore capability |
| **Partitioning** | Order table only | High volume, time-based queries |
| **Async Logging** | Recommended | Don't block user operations |
---
## Conclusion
This unified audit logging architecture provides:
**Complete traceability** across all data domains
**Regulatory compliance** with proper retention
**Performance optimization** through domain separation
**Flexibility** via JSON value storage
**Maintainability** with centralized service
The approach balances audit integrity with system performance, ensuring CLQMS can scale while maintaining comprehensive audit trails.
---
*Document Version: 1.0*
*Author: CLQMS Development Team*
*Date: February 19, 2026*