Use Case #3 Healthcare

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Proposer: ?

Consider consolidating with Agent AI as it will be used in Healthcare to assist patients and providers (doctors, nurses…)

1. Problems to solve:
   Inefficient data exchange between patients, providers, and institutions (data silos, incompatible formats).
   Lack of data security and privacy for patients (breaches, unauthorized access).
   Difficulty tracking the provenance of healthcare data (unclear data origin, modifications).
2. Weaknesses in the current practices:
   Paper-based records are prone to errors, loss, and difficulty sharing.
   Electronic health records (EHRs) can be complex, siloed, and lack interoperability.
   Data sharing often relies on faxing or emailing, which is insecure and lacks accountability.
3. How C2PA and TSP can help:
   C2PA tracks data provenance: Creates an audit trail for data, ensuring transparency and accountability.
   TSP enables secure and verifiable data distribution: Ensures data authenticity and allows patients to control what data is shared with whom.
4. Not in scope:
   Diagnosis or treatment of specific medical conditions.
   Development of new medical technologies.
   Regulatory compliance beyond HIPAA.

Data Examples:
Text: Medical summaries, doctor's notes, appointment details, medication instructions.
Video: Telehealth consultations, recorded physical therapy exercises.
Image: X-rays, MRIs, skin condition photos, CT Scans,.
AI Models: Personalized health predictions, risk assessments generated by AI algorithms, reading radiology reports.
User-specific health data: Blood pressure readings, weight measurements,fitness tracker data, lab results, prescriptions, vaccination history, surgeries.
Distribution with Authenticity and Privacy:
Data Creation: When Alice generates data (e.g., fills out a form, records a video consultation), her phone uses C2PA-compliant mechanisms to capture consent and provenance information. This includes timestamps, location data (optional), and cryptographic signatures for authenticity.
Data Storage: Alice's data is stored in her personal data pod within the TSP ecosystem. This pod is secured using private keys, ensuring only authorized entities can access it.
Data Sharing: When Alice needs to share data (e.g., with a doctor, insurance company), she creates a Time-Bound Sealed Package (TBSP) using TSP. This package contains the data, relevant provenance information, and access control policies specifying who can access it, for what purpose, and for how long.
Data Access: The recipient (e.g., doctor) uses their TSP client to request access to the TBSP. A user can approve or deny the request and set granular access permissions within the package. The doctor can then view the data within a secure enclave, ensuring confidentiality and data residency requirements.
Auditability: All data interactions are logged on the TSP blockchain, providing an immutable record of who accessed what data, when, and for what purpose. This transparency fosters trust and accountability.
Authorship Tracking:
C2PA-captured provenance information (timestamps, signatures) embedded within the data establishes user's authorship.
TSP logs record who created, shared, and accessed the data, further bolstering authorship traceability.
Privacy Considerations:
The user has complete control over her data through access control policies within TBSPs.
C2PA compliance ensures transparency and user rights regarding data collection and usage.
TSP's secure enclaves and cryptographic mechanisms protect data confidentiality and privacy.
The user can choose to share only specific data points within TBSPs, minimizing data exposure.