AI Evidence Pack Checklist for Private Healthcare Providers

Faisal Ali, AAISM, CISM, CRISC

When AI tools touch patient data, the organisation may be asked to show more than a policy. It may need evidence: what tools are in use, what data they process, what vendor terms apply, whether patients are informed, who reviews outputs and what the board has approved. This checklist shows the files and records a private healthcare provider may need when AI use is questioned by a DPO, board, insurer, MDO, CQC inspector, clinical lead or patient.

Who this is for

  • Private GP and GP-led clinics
  • Dental practices and groups
  • Doctor-led specialist clinics
  • Clinics using or planning ambient scribes
  • Practice managers, DPOs, boards and clinical governance leads

Board evidence

Checklist

  • AI tool inventory
  • One-page RAG exposure map
  • Board or partner AI risk note
  • Approved, conditional and prohibited use position
  • Named owner for AI governance
  • 30-day action plan

DPO and data protection evidence

Checklist

  • DPIA screening record
  • DPIA readiness note
  • Records of Processing Activities indicators
  • Vendor Data Processing Agreements
  • Data residency and sub-processor information
  • International transfer indicators
  • Privacy notice and patient transparency wording

Vendor evidence

Checklist

  • Supplier contract or terms
  • Data Processing Agreement
  • Sub-processor list
  • Hosting and data residency confirmation
  • Retention and deletion terms
  • Model-training position
  • Security assurance evidence
  • Supplier clinical safety evidence, where applicable

Ambient scribe evidence

Checklist

  • Scribe tool and licence tier
  • DPIA status
  • Patient explanation before use
  • Human-review workflow
  • Incident reporting route
  • Clinical safety ownership
  • Vendor evidence file

External review readiness

Checklist

  • MDO, PMI and insurer disclosure-readiness note
  • Incident process covering AI-related issues
  • Staff guidance on approved and prohibited use
  • Evidence of training or staff communication
  • Source and guidance mapping appendix

What ELSA AI can help produce

The Clinical AI Exposure Diagnostic™ creates the first board-ready version of this evidence pack in four working days from the start of delivery. Where an ambient scribe, AI transcription tool or consultation note-generation tool is in use, in trial or planned, the engagement routes to the Clinical AI Exposure Diagnostic with Ambient Scribe Assessment at £8,500. That engagement covers the full evidence pack plus a structured ambient scribe assessment. The £5,500 Standard Diagnostic does not apply where a scribe is in scope.

Outputs include

  • AI Tool and Use Case Inventory
  • Board Findings Report
  • RAG Exposure Map
  • Ambient Scribe Assessment Sheet
  • DPIA Readiness and Patient Data Exposure Note
  • Vendor Data Position and Evidence Tracker
  • MDO, PMI and Insurer Disclosure Readiness Note
  • 30-Day Priority Action Plan
  • Source and Guidance Mapping Appendix

The issue is not simply that AI tools exist. The issue is having no documented governance position when someone asks how that AI use is controlled. The Clinical AI Exposure Diagnostic™ page covers scope, timeline and fees.

ELSA AI provides advisory governance support only. It does not provide: legal advice or legal sign-off; CQC, ICO or NHS approval; insurer coverage or underwriting decisions; MDO indemnity decisions; a completed or signed DPIA; clinical safety case sign-off, DCB0160 authorship or appointment as Clinical Safety Officer; medical device or SaMD classification; certification or any guarantee of compliance. Final legal, data protection, clinical safety, regulatory, insurer and indemnity decisions remain with the client's DPO, legal counsel, Clinical Safety Officer, accountable officers and clinicians.

Need this evidence mapped for your clinic or group?

The Clinical AI Exposure Diagnostic™ gives clinic leadership a board-ready view of AI use, patient-data exposure, evidence gaps and priority actions in four working days from the start of delivery.

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