Mukherjee, Anurup, Shergill, Sukhi S., Ang, Chee Siang (2026) A clinician’s quick‑start guide to implementing digital health innovations in the NHS – with lessons from a UK-deployed AI stroke imaging decision-support software. Digital Health, 12 . ISSN 2055-2076. (doi:10.1177/20552076261437226) (KAR id:113542)
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| Official URL: https://doi.org/10.1177/20552076261437226 |
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Abstract
The successful implementation of digital health and artificial intelligence (AI) innovations in the National Health Service (NHS) requires more than technical development. Navigating regulation, generating decision-grade evidence, and meeting clinical safety, information-governance, and interoperability standards are critical steps that frequently delay or prevent adoption. This article presents a practical, implementation-focused roadmap designed to help clinicians, innovators, and healthcare leaders translate policy requirements into real-world NHS deployment. Drawing on guidance from the Medicines and Healthcare products Regulatory Agency (MHRA), the National Institute for Health and Care Excellence (NICE), and NHS Digital, we outline an eight-step pathway covering medical-device classification, value-proposition development, intended-purpose definition, regulatory approval, evidence generation, algorithmic fairness and generalisability, interoperability and information governance, and post-market surveillance. Unlike high-level digital health frameworks, the roadmap specifies minimum artefacts, typical ownership and sign-off responsibilities, and decision points aligned with NHS procurement and clinical governance processes. The roadmap is illustrated through a detailed case study of a UK-deployed AI stroke imaging decision-support software. Its progression from academic development to multi-site NHS deployment demonstrates how early regulatory engagement, robust real-world evaluation, and sustained clinical collaboration can support safe scaling and measurable service improvements, including increased access to reperfusion therapies and reduced inter-hospital transfer times. By distilling complex regulatory and evidence requirements into executable steps, this guide offers a clear route from idea to adoption. It emphasises that aligning regulation, evidence generation, bias mitigation, and interoperability from the outset is essential to sustainable digital health integration within the NHS.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1177/20552076261437226 |
| Uncontrolled keywords: | MHRA, interoperability and DTAC, artificial intelligence, NHS innovation, NICE evidence standards framework, health technology assessment, digital health |
| Subjects: | R Medicine |
| Institutional Unit: |
Schools > Kent and Medway Medical School Schools > School of Computing |
| Former Institutional Unit: |
There are no former institutional units.
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| Funders: | University of Kent (https://ror.org/00xkeyj56) |
| SWORD Depositor: | JISC Publications Router |
| Depositing User: | JISC Publications Router |
| Date Deposited: | 25 Mar 2026 15:50 UTC |
| Last Modified: | 26 Mar 2026 09:47 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/113542 (The current URI for this page, for reference purposes) |
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https://orcid.org/0009-0007-8742-463X
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