monitor-data-integrity
Über
Diese Fähigkeit unterstützt Entwickler beim Entwurf und der Implementierung eines Programms zur Überwachung der Datenintegrität für GxP-Systeme auf Grundlage der ALCOA+-Prinzipien. Sie bietet Anleitungen zur Einrichtung prüfender Kontrollen, zur Konfiguration der Anomalieerkennung für Muster wie Aktivitäten außerhalb der Arbeitszeiten sowie zur Einrichtung von Dashboards und Eskalationsverfahren. Nutzen Sie sie bei der Erstellung eines Compliance-Überwachungsprogramms, der Vorbereitung auf Inspektionen oder der Reaktion auf Vorfälle im Bereich der Datenintegrität.
Schnellinstallation
Claude Code
Empfohlennpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/monitor-data-integrityKopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren
Dokumentation
察數據完整
依 ALCOA+ 之則,建並行一程,以察驗證系統諸數據之完整,輔以察驗軌跡與異常之察。
用時
- GxP 系統欲建數據完整察程乃用
- 監管察驗將至而數據完整為焦點乃用
- 數據完整事故後,察須加強乃用
- 既有數據完整控制定期回顧乃用
- MHRA、WHO、或 PIC/S 數據完整指引欲行乃用
入
- 必要:在範系統及其 ALCOA+ 風險畫像
- 必要:適用指引(MHRA Data Integrity、WHO TRS 996、PIC/S PI 041)
- 必要:各系統當前之察驗軌跡能力
- 可選:先前數據完整察或監管察察
- 可選:既有察程或度量
- 可選:用者准入矩陣與角色定義
法
第一步:察當前 ALCOA+ 之姿
依 ALCOA+ 諸則察各系統:
# Data Integrity Assessment
## Document ID: DIA-[SITE]-[YYYY]-[NNN]
### ALCOA+ Assessment Matrix
| Principle | Definition | Assessment Questions | System 1 | System 2 |
|-----------|-----------|---------------------|----------|----------|
| **Attributable** | Who performed the action and when? | Are all entries linked to unique user IDs? Is the timestamp system-generated? | G/A/R | G/A/R |
| **Legible** | Can data be read and understood? | Are records readable throughout retention period? Are formats controlled? | G/A/R | G/A/R |
| **Contemporaneous** | Was data recorded at the time of the activity? | Are timestamps real-time? Are backdated entries detectable? | G/A/R | G/A/R |
| **Original** | Is this the first-captured data? | Are original records preserved? Is there a clear original vs copy distinction? | G/A/R | G/A/R |
| **Accurate** | Is the data correct and truthful? | Are calculations verified? Are transcription errors detectable? | G/A/R | G/A/R |
| **Complete** | Is all data present? | Are deletions detectable? Are all expected records present? | G/A/R | G/A/R |
| **Consistent** | Are data elements consistent across records? | Do timestamps follow logical sequence? Are versions consistent? | G/A/R | G/A/R |
| **Enduring** | Will data survive for the required retention period? | Is the storage medium reliable? Are backups verified? | G/A/R | G/A/R |
| **Available** | Can data be accessed when needed? | Are retrieval procedures documented? Are access controls appropriate? | G/A/R | G/A/R |
Rating: G = Good (controls adequate), A = Adequate (minor improvements needed), R = Remediation required
得: 各系統皆有評級之 ALCOA+ 察,每則皆有具體所察。 敗則: 系統不能受察者(如無察驗軌跡能力),標為要害缺,須立即補。
第二步:設察控
定察活以見數據完整之違:
# Detective Controls Design
## Document ID: DCD-[SITE]-[YYYY]-[NNN]
### Audit Trail Review Schedule
| System | Review Type | Frequency | Reviewer | Scope |
|--------|-----------|-----------|----------|-------|
| LIMS | Comprehensive | Monthly | QA | All data modifications, deletions, and access events |
| ERP | Targeted | Weekly | QA | Batch record modifications and approvals |
| R/Shiny | Comprehensive | Per analysis | Statistician | All input/output/parameter changes |
### Review Checklist
For each audit trail review cycle:
- [ ] All data modifications have documented justification
- [ ] No unexplained deletions or void entries
- [ ] Timestamps are sequential and consistent with business operations
- [ ] No off-hours activity without documented justification
- [ ] No shared account usage detected
- [ ] Failed login attempts are within normal thresholds
- [ ] No privilege escalation events outside change control
得: 察控有期、有人、有文,回顧之則明。 敗則: 察驗軌跡未按期回顧者,書其缺並上報質量之主管。漏察積險。
第三步:定異常察之模
立明確之模,觸發追察:
# Anomaly Detection Patterns
### Pattern 1: Off-Hours Activity
**Trigger:** Data creation, modification, or deletion outside business hours (defined as [06:00-20:00 local time, Monday-Friday])
**Threshold:** Any GxP-critical data modification outside defined hours
**Response:** Verify with user and supervisor within 2 business days
**Exceptions:** Documented shift work, approved overtime, automated processes
### Pattern 2: Sequential Modifications
**Trigger:** Multiple modifications to the same record within a short timeframe
**Threshold:** >3 modifications to the same record within 60 minutes
**Response:** Review modification reasons; verify each change has documented justification
**Exceptions:** Initial data entry corrections within [grace period, e.g., 30 minutes]
### Pattern 3: Bulk Changes
**Trigger:** Unusually high volume of data modifications by a single user
**Threshold:** >50 modifications per user per day (baseline: [calculate from normal usage])
**Response:** Verify business justification for bulk activity
**Exceptions:** Documented batch operations, data migration activities under change control
### Pattern 4: Delete/Void Spikes
**Trigger:** Unusual number of record deletions or voidings
**Threshold:** >5 delete/void events per user per week
**Response:** Immediate QA review of deleted/voided records
**Exceptions:** None — all delete/void events require documented justification
### Pattern 5: Privilege Escalation
**Trigger:** User access changes granting administrative or elevated privileges
**Threshold:** Any privilege change outside the user access management SOP
**Response:** Verify with IT security and system owner within 24 hours
**Exceptions:** Emergency access per documented emergency access procedure
### Pattern 6: Audit Trail Gaps
**Trigger:** Missing or interrupted audit trail entries
**Threshold:** Any gap > 0 entries (audit trail should be continuous)
**Response:** Immediate investigation — potential system malfunction or tampering
**Exceptions:** None — audit trail gaps are always critical
得: 諸模具體、可量、可行,閾與應有定。 敗則: 閾過低(多假陽)者,依基線校之。閾過高(漏實情)者,首察週期後緊之。
第四步:建度量盤
# Data Integrity Metrics Dashboard
## Document ID: DIMD-[SITE]-[YYYY]-[NNN]
### Key Performance Indicators
| KPI | Metric | Target | Yellow Threshold | Red Threshold | Source |
|-----|--------|--------|-----------------|---------------|--------|
| DI-01 | Audit trail review completion rate | 100% | <95% | <90% | Review log |
| DI-02 | Anomalies detected per month | Trending down | >10% increase MoM | >25% increase MoM | Anomaly log |
| DI-03 | Anomaly investigation closure rate | <15 business days | >15 days | >30 days | Investigation log |
| DI-04 | Open data integrity CAPAs | 0 overdue | 1-2 overdue | >2 overdue | CAPA tracker |
| DI-05 | Shared account instances detected | 0 | 1-2 | >2 | Access review |
| DI-06 | Unauthorised access attempts | <5/month | 5-10/month | >10/month | System logs |
| DI-07 | Audit trail gap events | 0 | N/A | >0 (always red) | System monitoring |
### Reporting Cadence
| Report | Frequency | Audience | Owner |
|--------|-----------|----------|-------|
| DI Metrics Summary | Monthly | QA Director, System Owners | QA Analyst |
| DI Trend Report | Quarterly | Quality Council | QA Manager |
| DI Annual Review | Annual | Site Director | QA Director |
得: 度量盤一目可見合規之態,升級之觸明。 敗則: 數據源不能支自動度量者,先以人工收集,書計劃以動之。
第五步:立追察觸發與升級
# Investigation and Escalation Matrix
### Investigation Triggers
| Trigger | Severity | Response Time | Investigator |
|---------|----------|---------------|-------------|
| Audit trail gap detected | Critical | Immediate (within 4 hours) | IT + QA |
| Confirmed data falsification | Critical | Immediate (within 4 hours) | QA Director |
| Anomaly pattern confirmed after review | Major | Within 5 business days | QA Analyst |
| Repeated anomalies from same user | Major | Within 5 business days | QA + HR |
| Overdue audit trail review | Minor | Within 10 business days | QA Manager |
### Escalation Path
| Level | Escalated To | When |
|-------|-------------|------|
| 1 | System Owner | Any confirmed anomaly |
| 2 | QA Director | Major or critical finding |
| 3 | Site Director | Critical finding or potential regulatory impact |
| 4 | Regulatory Affairs | Confirmed data integrity failure requiring regulatory notification |
得: 各察有定之嚴、時、升級路。 敗則: 察未於定時內畢者,升至下一級。
第六步:合察計劃
集諸件為主數據完整察計劃:
# Data Integrity Monitoring Plan
## Document ID: DI-MONITORING-PLAN-[SITE]-[YYYY]-[NNN]
### 1. Purpose and Scope
[From assessment scope]
### 2. ALCOA+ Assessment Summary
[From Step 1]
### 3. Detective Controls
[From Step 2]
### 4. Anomaly Detection Rules
[From Step 3]
### 5. Metrics and Reporting
[From Step 4]
### 6. Investigation and Escalation
[From Step 5]
### 7. Periodic Review
- Monitoring plan review: Annual
- Anomaly thresholds: Adjust after each quarterly review
- ALCOA+ re-assessment: When systems change or new systems are added
### 8. Approval
| Role | Name | Signature | Date |
|------|------|-----------|------|
| QA Director | | | |
| IT Director | | | |
| Site Director | | | |
得: 一已批之文,定完整數據完整察程。 敗則: 計劃過大難以一文承者,建主計劃並引特定系統察程。
驗
- 諸在範系統皆畢 ALCOA+ 察
- 察驗軌跡回顧期、範圍、責人皆定
- 至少五異常察模有定,閾明確
- 度量盤具 KPI,綠黃紅閾分明
- 追察觸發有定,嚴與應時皆明
- 升級矩陣達於監管事務(要害察時)
- 察計劃經 QA 與 IT 主管核准
- 定期回顧之期已立
陷
- 察而無行:收度量而不察異,給虛假安全感,劣於不察(生有所漏察之據)。
- 靜閾:以揣測非基線數據定閾者,多假陽,致警疲。
- 察驗軌跡如打勾:回顧而不知所察,無效。訓回顧者於異常之模。
- 忽系統限:某些系統察驗軌跡能力差。書其限,行補償控,勿假裝其無。
- 無趨勢:個別異常或微,然跨時跨人之模顯系統病。必趨勢化數據完整度量。
參
design-compliance-architecture— 識需數據完整察之系統implement-audit-trail— 察所依之技基investigate-capa-root-cause— 察測得問題需正式追察時conduct-gxp-audit— 察察察程之效prepare-inspection-readiness— 數據完整為監管察驗主焦點
GitHub Repository
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