AI Action Assurance for Healthcare

Make healthcare AI reviewable.

DigiTrust helps healthcare organizations connect source evidence, repeatable checks, clinician or accountable human approval, approved use, known limits, and a complete review history across important AI workflows.

Begin with a defined review workflow, synthetic evidence, and an accountable human owner. Clinical judgment, privacy, security, and existing AI governance remain with the customer.

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30–45 day pilot2–3 AI workflowsNo protected health information required for initial discoveryAWS Marketplace purchasing

The healthcare AI trust challenge

Human oversight is essential. The evidence behind it must be reviewable.

Healthcare organizations already maintain meaningful controls around patient safety, privacy, clinical authority, quality, research, security, and compliance. As AI enters clinical, administrative, research, and patient-facing workflows, those controls need an operational record that shows how they worked in practice.

DigiTrust preserves the review path. It does not make clinical decisions, replace clinicians, provide legal advice, certify regulatory compliance, or override customer governance.

Two synthetic reference workflows

Make the handoff small enough to verify.

Both references end at a simulated internal review queue. They demonstrate evidence and approval controls without sending a referral, changing a clinical note, or connecting to an electronic health record.

01 / REFERRAL INTAKE

Review an administrative handoff

An intake team prepares a summary from synthetic referral evidence. A different authorized reviewer checks the support and approves a defined receiving queue.

Bind the source references and workflow policy.
Check required evidence and preserve unresolved gaps.
Approve the exact result, purpose, and queue.
Record one handoff and inspect its outcome after a lost response.

Output: A reviewable evidence and approval record
Blocked example: A changed destination or missing approval
Customer decision still needed: Workflow owner, required evidence, receiving system, and data scope

02 / DOCUMENTATION EVIDENCE

Review the support behind a draft

A documentation team links a synthetic draft to supporting sources. A separate reviewer evaluates the exact evidence packet and authorizes its handoff to a review queue.

Identify the draft, sources, policy, and intended use.
Check support and record corrections without erasing history.
Require independent approval of the final reviewed version.
Recover the recorded outcome without repeating the handoff.

Output: A version-bound documentation review record
Blocked example: Self-approval or a changed source reference
Customer decision still needed: Review roles, documentation policy, source access, and retention

Scope of the examples: Synthetic workflow checks provide engineering evidence. They do not establish clinical validity, customer acceptance, or production readiness. Review the shared architecture and remaining acceptance work.

Further discovery areas

Assess the wider workflow after the first bounded reference.

These are candidate discovery areas. Each needs its own workflow assessment, customer authorization, integration design, and acceptance criteria.

01 / DOCUMENTATION

Ambient clinical documentation

Record where source information came from, provider review, patient choice, corrections, retention rules, known limits, and note history.

02 / RESEARCH

Clinical research and trial matching

Connect source evidence, eligibility rules, recommendation context, human review, known limits, approval, and a complete decision history.

03 / PATIENT

Patient communication and digital health

Record where content and data came from, the approved purpose, personalization rules, human escalation, known limits, and accountability.

04 / OPERATIONS

Administrative and operational AI

Review scheduling, automation, knowledge assistants, data and tool access, approval, exception handling, and review evidence.

05 / INNOVATION

Healthcare AI innovation programs

Preserve evaluation evidence, success criteria, safety checks, deployment approval, known limits, rollback decisions, and evidence for expansion.

06 / CLINICAL SUPPORT

Clinical decision assistance

Connect source evidence, AI-system context, checks, clinician approval, recommendation limits, exceptions, and the final accountable decision.

The DigiTrust healthcare trust record

Make existing human-review and governance controls operationally visible.

01 / EVIDENCE

Source and workflow history

Identify what information, systems, models, tools, and events influenced the AI-assisted result.

02 / VERIFY

Repeatable, rule-based checks

Record clear checks for integrity, quality, supporting facts, approval rights, conflicts, and safe disclosure.

03 / AUTHORITY

Clinician or accountable human approval

Record the reviewer, role, approved purpose, conditions, decision, and time period.

04 / PURPOSE

Approved-use boundaries

Show whether the AI was used for the approved purpose and stop changed or withdrawn use from inheriting approval.

05 / REVIEW

Known limits and review history

State uncertainty and unavailable evidence clearly and preserve the history for governance, quality, privacy, security, or later review.

Healthcare Pilot

Evaluate two to three consequential workflows in 30–45 days.

DigiTrust Enterprise AI Evidence and Assurance Pilot

Begin with high-level workflow context and synthetic examples. Patient-identifiable data, clinical recordings, credentials, and protected health information remain out of the initial discovery path.

Commercial termsCustomer-specific

Scope2–3 workflows

PurchasingAWS Marketplace

ExpansionProduction pathway

Scope the pilot Review purchasing

1
Workflow and control assessment
Current clinical or operational use, evidence, governance, authority, privacy, and review state.
2
Evidence and assurance map
Sources, checks, approvals, patient-choice or purpose boundaries, exceptions, and limitations.
3
Production roadmap
Prioritized implementation design, operating controls, data handling, success criteria, and expansion.
4
Executive findings
Customer-safe outputs for clinical, digital, privacy, security, compliance, risk, and purchasing teams.

Who should participate

Bring the people who own the workflow, patient or business consequence, and accountable authority.

Chief Digital or Transformation Officer

Chief Information Officer

Chief Medical Information Officer

Clinical Informatics

AI Governance

Privacy and Compliance

Information Security

Enterprise Risk or Internal Audit

Workflow Clinical or Operational Sponsor

Data and safety boundaries

Start with the workflow—not sensitive patient data.

01 / DISCOVERYNo protected health information required

Initial discovery uses high-level workflows and synthetic examples. A later data decision defines any approved customer information.

02 / HUMAN REVIEWClinical judgment remains human

DigiTrust records and supports human approval; it does not replace clinical judgment.

03 / EXISTING CONTROLSExisting controls remain primary

Privacy, security, quality, ethics, legal, and compliance teams retain their responsibilities.

04 / EXPANSIONSensitive data requires approval

Any later data handling depends on contracts, architecture, access controls, security requirements, and customer authorization.

Buying through AWS Marketplace

A credible purchasing path for an enterprise healthcare pilot.

DigiTrust is publicly listed in AWS Marketplace. For qualified opportunities, DigiTrans can work with the customer and AWS teams to confirm how AWS is involved, the implementation approach, healthcare-specialist participation, purchasing, and production expansion.

AWS Marketplace availability does not imply AWS endorsement or a guarantee of clinical, patient-safety, security, privacy, regulatory, or business outcomes.

Start with one reviewable workflow

Make healthcare AI easier to govern, explain, and expand.

Request a 30-minute briefing to identify the strongest workflow, accountable stakeholders, information needed for review, how AWS is involved, and the pilot path.

Request the briefing View on AWS Marketplace