Professor David Snead

University Hospitals of Coventry and Warwickshire NHS Trust

Professor Snead is a consultant pathologist at the University Hospitals Coventry and Warwickshire and Professor of Pathology Practice at the University of Warwick. He has been in post at Coventry for 20 years. He is the founding director of PathLAKE, one of the five Innovate UK funded centres of excellence for the development of artificial intelligence in digital pathology and radiology.
He is an international expert in the use of digital pathology having led Coventry to be one of the first hospitals in Europe to switch to digital pathology for routine diagnosis. His team published the worlds largest validation study on the use of digital pathology, and which was awarded the 2016 Roger Cotton Prize for best paper in Histopathology.
Prior to leading PathLAKE Prof Snead was for many years the clinical lead for cellular pathology at UHCW. This experience has given him a unique understanding of how innovative AI based solutions can be deployed to address the major challenges facing cellular pathology department across the NHS.
There are no shortcuts to achieving excellent results in AI solutions, but a career’s experience in diagnostic cellular pathology gives the understanding of where this kind of innovation can be best deployed for maximal gains in quality and efficiency.

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Digital Pathology – the scope and potential return on investment.

Transition from glass slide reporting to digital pathology requires significant investment in equipment and staff in cellular pathology laboratories. There are numerous potential advantages in making this transition but accurate data on the return on investment delivers is difficult to assimilate for a number of reasons. Detailed studies are scarce and often data is estimated from studies designed for other purposes. Assumptions applied may not be relevant to local situations. Costing some benefits of digitisation such as improved accuracy of reporting through better subspecialisation or peer review of cases present a particularly complex problem, involving the measuring the cost of errors made against costs of delivering accurate diagnosis. This work is rarely reported partly because identifying error in existing workflow is itself a challenge.
The PathLAKE project along with many other initiatives, is developing artificial intelligence-based solutions to common cellular pathology workflow challenges. The arrival of such technology adds additional complexity, and, very likely, will itself lead to radical changes in the way cellular pathology is practised which may be disruptive to the current provision of services.
Service leads and healthcare planners need to be aware of the scale changes coming and to rapidly develop an understanding of how these advances are likely to impact their services.
This paper reviews what evidence is available and what additional value from this data could be delivered to address local requirements.


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