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Published on: July 14, 2023
Large scale implementation of DP for clinical diagnoses: experience, challenges, and lessons learned
Blaise Clarke1, Charlotte Carment-Baker1,2, Christine Bruce1,2
1Laboratory Medicine Program, University Health Network, Toronto, Canada.
Abstract:
Implementing DP on a large scale is a complex, multi-dimensional process that requires strategic planning, technological adaptation, and change management. We provide a detailed account of the full-scale implementation of DP at the University Health Network (UHN), a multi-site tertiary clinical center in Canada, highlighting practical lessons learned, ongoing challenges, and mitigation strategies.
Abstract:
A phased implementation approach was adopted, involving pre-implementation planning, procurement, infrastructure development, and optimized validation protocols. Significant focus was placed on technical considerations, including system interoperability, storage capacity, and image quality. Procurement was structured to ensure vendor neutrality and long-term sustainability.A critical component of the implementation was "change management", addressing resistance to change through extensive training, real-time troubleshooting, utilizing "super users" as change champions. Attention was paid to pathologist office configuration.
Abstract:
A dual workflow model, with simultaneous access to both glass and digital slides, facilitated smoother transition. As of this writing all histopathology H&E cases and tissue hematopathology are being scanned. Efforts to implement digital liquid hematopathology and cytopathology are ongoing.
Abstract:
The financial implications of DP implementation were evaluated, including direct and indirect costs. While initial investments in scanners, storage, and software infrastructure were substantial, long-term savings are anticipated through increased efficiency, reduced physical slide storage, enhanced workload distribution and the integration of AI-based tools.
Abstract:
Continuous monitoring and feedback were established to assess system performance and address emerging challenges. Scalability and future applications of DP remain a priority. The adoption of AI-driven pathology tools, remote diagnostics, and cross-institutional data sharing are anticipated to further enhance the value of DP. UHN's experience underscores the importance of a structured, multidisciplinary approach to DP implementation.
Abstract:
Our experience offers a realistic and evolving roadmap for institutions considering DP adoption. We provide practical guidance, highlight persistent challenges and emphasize the importance of continuous evaluation and adaptation.
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