Patient care navigation and health copilot AI
Health-GPT
Health-GPT offers patient-directed record comprehension and preparation. Readable FAQ and privacy material support a qualified assessment. The terms could not be retrieved, and the earlier app-store discrepancy remains historical.
Published September 8, 2026 as an AI-assisted draft. The public report separates documented facts, agency judgments and unresolved questions.
Summary judgment · 80 out of 100 toward patient-directed
Omni Timeline LLC's patient record-comprehension and visit-preparation app, not other similarly named GPT products. Preserve August 15 baseline 80.
Potentially agency-expanding, with vendor-opacity and disclosure caveats
Health-GPT offers patient-directed record comprehension and preparation. Readable FAQ and privacy material support a qualified assessment. The terms could not be retrieved, and the earlier app-store discrepancy remains historical.
Patient agency
How this tool changes agency
Visit-question preparation can support the patient's own reasoning and participation. A readable timeline must remain checkable against original documents, especially for dates and medications. Deleting an entry is not the same as correcting an extraction.
Output correction, export, named processors, operative terms, current store label and extraction quality remain unresolved.
Patient agency assessment
Who sets and changes the goal?
Patients select records, questions and excluded entries. The exclusion control is meaningful, but it controls answer context rather than proving that an upload was never processed or retained. Generated timeline correction remains unestablished.
What can the patient understand, question, or do?
Visit-question preparation can support the patient's own reasoning and participation. A readable timeline must remain checkable against original documents, especially for dates and medications. Deleting an entry is not the same as correcting an extraction.
Can the patient evaluate the conditions of use?
Current policy statements support the existing qualified assessment but leave the processing parties and usable exit formats unclear. The newly readable FAQ resolves a retrieval gap without validating clinical behavior.
Text findings
Conditions of use
Published controls and their limits
Current policy statements support the existing qualified assessment but leave the processing parties and usable exit formats unclear. The newly readable FAQ resolves a retrieval gap without validating clinical behavior.
What remains unknown?
Not tested or not established
Output correction, export, named processors, operative terms, current store label and extraction quality remain unresolved.
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
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
Output correction, export, named processors, operative terms, current store label and extraction quality remain unresolved. 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 · Low to medium for public design and policy, low for implementation (AI-assisted draft)