Blockchain Audit Trails Resolve the Electronic Health Record Traceability Problem Created by Generative AI
As large language models generate clinical documentation at scale, electronic health records increasingly contain AI-produced content with no verifiable provenance. The field has named this traceability gap but has not yet specified an architectural solution. Blockchain-based audit logging — append-only, cryptographically chained, and tamper-resistant — provides the answer: a lightweight layer capturing model identity, prompt hash, output fingerprint, and timestamp at generation, creating a verifiable chain of custody before text enters the clinical record. Adopting blockchain audit logging as a standard condition of institutional large language model deployment would resolve this traceability crisis before it becomes irreversible.
Authors
- Thomas F Heston (ORCID: https://orcid.org/0000-0002-5655-2512)
Institutions
- University of Washington (US)
- Washington State University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-21
- DOI
- https://doi.org/10.5281/zenodo.20337357
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00