Beyond Validation: Operationalising Post-Deployment Surveillance of AI Medical Devices in Clinical Practice.

Jesus A Perdomo Lampignano^1,2, Aditya Kale^3,4, Shamie Kumar⁵, Dhruv Shah⁵, Bhargava Reddy⁵, David J Lowe^6,7

¹Department of Radiology, Queen Elizabeth University Hospital, NHS Greater Glasgow & Clyde, Glasgow, UK.

²School of Medicine, Dentistry & Nursing, University of Glasgow, Glasgow, UK.

³College of Medicine and Health, University of Birmingham, Birmingham, UK.

⁴National Institute for Health and Care Research, Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, UK.

⁵Qure.AI Technologies Private Limited, London, UK.

⁶HealthTech Innovation & Translation Lab, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK. david.lowe@glasgow.ac.uk.

⁷Emergency Department, Queen Elizabeth University Hospital, Glasgow, UK. david.lowe@glasgow.ac.uk.

PubMed DOI

Abstract

Artificial intelligence medical devices are increasingly deployed in clinical practice, yet practical approaches to post-deployment monitoring remain poorly defined. We present a structured, decision-oriented approach to monitoring within healthcare institutions, grounded in our own deployment experience. By framing surveillance as a set of interdependent decisions, this model supports effective p…

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