Digital Pathology Archives as Long-Term Clinical Memory: A Self-Sovereign Identity-Based Governance Model.

Background/

Objectives

Digital pathology is transforming diagnostic workflows through whole-slide imaging (WSI), digital archiving, artificial intelligence (AI)-assisted analysis, and remote consultation. The existing literature only partly addresses patient access to pathology records and cross-institutional sharing within a holistic governance framework. This study proposes a Self-Sovereign Identity (SSI)-based conceptual governance model that treats digital pathology archives as components of long-term clinical memory. Here, clinical memory refers to a pathology-specific information layer that preserves record context, provenance, integrity, and longitudinal links across time and institutions while supporting governed reuse and legally bounded patient-managed access.

Methods

Eighty publicly available complaints from the Şikayetvar platform were examined using codebook-based thematic content analysis. Aggregated National Health Service (NHS) Written Complaints data were used to provide an illustrative external governance context. These data were not used for cross-country prevalence comparison or corroboration.

Results

The main complaint themes were absent or inaccessible pathology results (66.3%) and records that remained unavailable despite notifications that the results were ready (55.0%). Complaint themes, the literature, regulatory sources, technical standards, and internal clinical review were synthesized while preserving different analytical functions, and 11 governance requirements were identified.

Conclusions

Developed through Design Science Research, the model integrates verifiable credentials (VCs), a patient digital wallet, purpose- and time-limited authorization, dynamic consent and access revocation, secure off-chain storage, and blockchain-based integrity and auditing. The model was examined through an internal requirement-coverage assessment and a supplementary post hoc benchmark-oriented assessment. These analyses indicate conceptual consistency rather than independent validation. Real-world technical, clinical, usability, security, and equity validation remains necessary.