DIGITAL PATHOLOGY


handle large amounts of unstructured data (like images) whilst also providing good scalability at a reasonable price. This in turn will position the region well to create a large database of WSIs that can potentially be mined for larger-scale research purposes.


Networks such as Granada University Hospitals have published reports detailing how these networks operate, providing details such as the length of time images spend in different storage tiers.8 Whilst the UK market has made strides, many laboratories still do not retain their images long term. As the market transitions towards capturing a higher percentage of the primary diagnostic workflow it would do well to look towards addressing storage in a more consolidated manner. As explained in an earlier article, digital pathology image storage is no simple topic, and moving forwards will require gathering as much information as possible from prior implementations as examples on the topic.


Examples of DP implementations There are multiple reasons laboratories worldwide may choose to convert to digital workflows (Fig 2). However, not all will appeal to every potential market, provider and individual laboratory, which is part of the reason adoption has been so sporadic between laboratory types and applications.


It should be noted in today’s market it may not make sense for all institutions to progress to 100% digitisation immediately. Indeed, many private laboratories worldwide have chosen to adoption DP for a subsegment of applications that allow DP AI to support workflows, such as breast or prostate. This relatively slow uptake is thought to be driven by a desire to see financial return- on-investment, rather than efficiency, with some vendors believing that only once AI is adopted will the industry realise the true benefits of pathology digitisation. Benefits aside, whilst significant strides have been made recently in the UK in terms of digital pathology penetration, pathologist acceptance and DICOM standardisation, there are still challenges ahead. The most significant barrier to DP adoption worldwide remains the substantial expenditure associated, and mistakes when investing can be extremely costly. Mis-steps lead to delayed and/ or inefficient implementations, which in turn impacts the perceived benefits of digitisation.


As the world looks to the UK market as a leading example for DP implementation at scale, now it is more crucial than ever


Data Monetisation


• Most $$$ • GDP concerns • Needs good research- clinical integration


Reimbursement


• Little for DPath • Long process • Liable to reductions


Immediate Money Saved


• Still need to make slides • Possible costs on transport averted • Possbile savings with AI


Prestige


• Matters to few • Harder to value • Easy to lose


Fig 2. Types of return on investment for digital pathology providers.


to reach out to peers, learn where and how success is derived and invest as much as possible in solutions that future- proof investments.


Specific markets and institutions have been noted by the industry to be making advances in certain areas, and the UK market would do well to pay attention and apply lessons learned closely.


References 1 The Royal College of Pathologists. College


report finds UK-wide histopathology staff shortages. (RCPath, 2019). https://www.rcpath.org/discover- pathology/news/college-report-finds- severe-staff-shortages-across-services-vital- to-cancer-diagnosis.html


2 Institute of Biomedical Science. IBMS Long Term Workforce Plan. (IBMS, 2023). https://www.ibms.org/resources/ documents/ibms-long-term-workforce-plan/


3 Fokkema IFAC, van der Velde KJ, Slofstra MK et al. Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data. Hum Mutat. 2019;40(12):2230-2238. doi:10.1002/ humu.23896


4 Casparie M, Tiebosch AT, Burger G et al. Pathology databanking and biobanking in The Netherlands, a central role for PALGA, the nationwide histopathology and cytopathology data network and archive. Cell Oncol. 2007;29(1):19-24. doi:10.1155/2007/971816


5 Professional Record Standards Body. Pathology Strategic Activities. (PRSB, 2021). https://theprsb.org/wp-content/ uploads/2021/03/Pathology-Final-Draft- Report-V1.0.pdf


6 Ang A. Using 5G to cut down diagnostic WWW.PATHOLOGYINPRACTICE.COM APRIL 2024 49


reading by half. (Healthcare IT News, 2023). https://www.healthcareitnews.com/ news/asia/using-5g-cut-down-diagnostic- reading-half


7 NHS Digital. NHS England launches tech trials to boost health and care connectivity. (NHS, 2023). https://digital.nhs.uk/ news/2023/nhs-england-launches-tech- trials-to-boost-health-and-care-connectivity


8 Retamero JA, Aneiros-Fernandez J, Del Moral RG. Complete Digital Pathology for Routine Histopathology Diagnosis in a Multicenter Hospital Network. Arch Pathol Lab Med. 2020;144(2):221-228. doi:10.5858/arpa.2018-0541-OA


Imogen Fitt is a Senior Market Analyst at Signify Research. Imogen joined Signify in 2018 as part of the Healthcare IT team. She holds a First-class Biomedical Sciences degree from the University of Warwick where her studies included molecular biology and pharmacology. Since joining the team Imogen has studied the medical imaging software and hardware markets and is now expanding Signify Research’s Diagnostics and Life Sciences coverage.


Signify Research provides health technology market intelligence, blending insights collected from in-depth interviews with technology vendors and healthcare professionals with sales data reported to us by leading vendors to provide a complete and balanced view of the market trends. Its coverage areas are Medical Imaging, Clinical Care, Digital Health, Diagnostic and Lifesciences and Healthcare IT.


01234 986111 enquiries@signifyresearch.net www.signifyresearch.net


Value from digital pathology (What providers will pay for)


Direct (Financial)


Better Outcome (Patient)


• Harder to measure • Longer-term realisation • Larger “savings” than immediate savings


Increased Worker Productivity (Pathologist)


• Matters to few • Harder to value • Easy to lose


Indirect (Operational)


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57