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

Vollständiger Abstract

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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.