Implementing digital pathology: qualitative and financial insights from eight leading European laboratories

Digital Pathology (DP) revolutionizes the diagnostic workflow. Digitized scanned slides enhance operational efficiency by facilitating remote access, slide storage, reporting and automated AI image analysis, and enabling collaboration and research. However, substantial upfront and maintenance costs remain significant barriers to adoption. This study evaluates DP's financial and qualitative value, exploring whether the long-term financial benefits justify investments and addressing implementation challenges in large public and private European laboratory settings. A targeted literature review, semi-structured interviews, surveys, and a net present value (NPV) model were employed to assess DP's impact on clinical practice and laboratory financials. Qualitative findings validate the key benefits of DP, including optimized workflow, enhanced logistics, and improved laboratory organization. Pathologists reported a smooth integration, improved training, teaching, and research capabilities, and increased flexibility through remote work. Collaboration within multidisciplinary teams was strengthened, while case examination efficiency and access to archival slides were notably improved. Quantitative results indicate that DP demonstrates strong financial potential, achieving cost recovery within 6 years. DP investment results in a 7-year NPV of + €0.21 million (m) driven by increased productivity and diagnosis volumes. Although the high upfront costs for scanners, training, and system integration pose a significant barrier to the adoption of DP, larger institutions are better positioned to leverage economies of scale. This study underscores the importance of sustained financial support to cope with the initial investment and regional collaboration in driving widespread adoption of DP. Expanding reimbursement policies for pathology procedures could significantly reduce financial barriers.

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Publication Details

Journal
Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin
Published
2025-03-08
DOI
https://doi.org/10.1007/s00428-025-04064-y
Citations
15
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
37.21

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article

Implementing digital pathology: qualitative and financial insights from eight leading European laboratories

Sven Mattern, Federico Rojo, H. M. Bannister, A. Gkiokas et al.
15 citations
Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin
AI in cancer detection
37.21
article

Implementing digital pathology: qualitative and financial insights from eight leading European laboratories

Sven Mattern, Federico Rojo, H. M. Bannister, A. Gkiokas, Elena Guerini‐Rocco, Elizabeth A. Sheppard, Christian M. Schürch, Angelo Paolo Dei Tos, Thomas di Maio, Nicola Fusco, Falko Fend, Nicola Antonio Martino, Manuel Salto‐Tellez, Pedro Carríón López, Marie Brevet, Xavier Matías‐Guiu, Jordi Temprana‐Salvador, David Snead, Nathalie Rioux‐Leclercq, David Clark, Solène-Florence Kammerer-Jacquet, Silvia Ramírez-Peinado, Mario Arpaia, Ons Ben Dhia
article en
15 citations

Abstract

Digital Pathology (DP) revolutionizes the diagnostic workflow. Digitized scanned slides enhance operational efficiency by facilitating remote access, slide storage, reporting and automated AI image analysis, and enabling collaboration and research. However, substantial upfront and maintenance costs remain significant barriers to adoption. This study evaluates DP's financial and qualitative value, exploring whether the long-term financial benefits justify investments and addressing implementation challenges in large public and private European laboratory settings. A targeted literature review, semi-structured interviews, surveys, and a net present value (NPV) model were employed to assess DP's impact on clinical practice and laboratory financials. Qualitative findings validate the key benefits of DP, including optimized workflow, enhanced logistics, and improved laboratory organization. Pathologists reported a smooth integration, improved training, teaching, and research capabilities, and increased flexibility through remote work. Collaboration within multidisciplinary teams was strengthened, while case examination efficiency and access to archival slides were notably improved. Quantitative results indicate that DP demonstrates strong financial potential, achieving cost recovery within 6 years. DP investment results in a 7-year NPV of + €0.21 million (m) driven by increased productivity and diagnosis volumes. Although the high upfront costs for scanners, training, and system integration pose a significant barrier to the adoption of DP, larger institutions are better positioned to leverage economies of scale. This study underscores the importance of sustained financial support to cope with the initial investment and regional collaboration in driving widespread adoption of DP. Expanding reimbursement policies for pathology procedures could significantly reduce financial barriers.

Archiv für Pathologische Anatomie und Physiologie und für Klinische MedicinVol. 487(4)
AstraZeneca (United Kingdom) (GB), Queen's University Belfast (GB), Nottingham University Hospitals NHS Trust (GB), University of Padua (IT), Universitat de Lleida (ES), Bellvitge University Hospital (ES), Hospital Universitari Arnau de Vilanova (ES), University of Warwick (GB), Institut d'Investigació Biomédica de Bellvitge (ES), Research Institute for Work, Technology and Culture (DE), University Children's Hospital Tübingen (DE), Vall d'Hebron Hospital Universitari (ES), Coventry (United Kingdom) (GB), AstraZeneca (Switzerland) (CH), Hospital Universitario Fundación Jiménez Díaz (ES), AstraZeneca (Spain) (ES), Institut Català de la Salut (ES), Centre Hospitalier Universitaire de Rennes (FR), Centro de Investigación Biomédica en Red de Cáncer (ES), Université de Rennes (FR), European Institute of Oncology (IT)
AstraZeneca
Openalex Percentile: Top 0%
AI in cancer detection
37.21
DOIOpen Access PDFOpenAlex
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