Patient care navigation and health copilot AI
Advoca
Advoca lets patients and care partners record visits, ask questions, and share information. Its Washington consumer health policy ties free access to research consent, with paid access after withdrawal. The policy and homepage give conflicting accounts of audio processing.
Published September 8, 2026 as an AI-assisted draft. The public report separates documented facts, agency judgments and unresolved questions.
Summary judgment · 84 out of 100 toward patient-directed
Patient/carer-selected Advoca app for recording, preparation, health questions, and research participation. Vendor-hosted consumer assistance, with a distinct research-commercialization channel.
Potentially agency-expanding, with research-access and processing qualifications
Advoca lets patients and care partners record visits, ask questions, and share information. Its Washington consumer health policy ties free access to research consent, with paid access after withdrawal. The policy and homepage give conflicting accounts of audio processing.
Patient agency
How this tool changes agency
Source-linked answers and retained originals could help users check summaries and prepare challenges. Actual source matching and correction are untested.
Whether the tier conditions apply identically outside Washington, actual audio routing, transcript correction, and post-anonymization withdrawal effects.
Patient agency assessment
Who sets and changes the goal?
Patients choose questions, records, and recipients. Consent withdrawal is documented but has a financial consequence for free-tier users. That is a substantive condition on continued access, not simply optional research alongside identical free service.
What can the patient understand, question, or do?
Source-linked answers and retained originals could help users check summaries and prepare challenges. Actual source matching and correction are untested.
Can the patient evaluate the conditions of use?
The detailed policy enables scrutiny, but its account of processing differs from a prominent privacy promise. Research consent and model-training use should be visible before reliance.
Text findings
Conditions of use
Published controls and their limits
The detailed policy enables scrutiny, but its account of processing differs from a prominent privacy promise. Research consent and model-training use should be visible before reliance.
What remains unknown?
Not tested or not established
Whether the tier conditions apply identically outside Washington, actual audio routing, transcript correction, and post-anonymization withdrawal effects.
Who evaluated this?
AI-assisted public-source draft
Vendor statements describe published conditions, not independently verified behavior. No clinical, security, accessibility, or legal validation is claimed. Earlier evidence remains dated in the report and history.
Sources checked
- https://advocahealth.com/
- https://advocahealth.com/consumer-health-data-privacy-policy.html
- https://advocahealth.com/terms/
Source-specific findings and retrieval limitations are recorded in the full report.
Review provenance
Criteria
CAIHL-derived HugoScore framework and September 7 qualitative review priorities. Draft v1.2 numerical anchors remain unadopted.
Reviewer
AI-assisted public-source reassessment prepared in OpenAI Codex.
AI / model
OpenAI Codex / GPT-6
Human review
Hugo Campos authorized publication of these AI-assisted draft reassessments on September 8, 2026. This does not claim comprehensive human verification of every finding.
Review date
2026-09-08
Limitations
Whether the tier conditions apply identically outside Washington, actual audio routing, transcript correction, and post-anonymization withdrawal effects. No live product use, patient-data upload, account creation, code audit, clinical evaluation, or independent implementation validation.
Review method
Focused public-source reassessment using CAIHL: patient authority, critical capacity, and informed control. Existing evidence plus one focused primary-source pass and at most one targeted follow-up. No live product testing. Numerical scores remain provisional editorial placements, not a new calculation.
AI-assisted draft · Medium for published conditions, low for implementation (AI-assisted draft)