AI-Enabled Digital Health
Enhancing NEWS2 for Earlier Detection of Clinical Deterioration
Status: Active
Collaborator: Dr Chris Plummer, Consultant Cardiologist and Chief Clinical Informatics Officer, Newcastle upon Tyne Hospitals NHS Foundation Trust
The National Early Warning Score (NEWS2) is the standard tool for identifying deteriorating patients in NHS hospitals, but its predictive accuracy beyond 24 hours is limited, particularly in older adults who were underrepresented in its development. Working with Dr Chris Plummer and routinely collected data from Newcastle Hospitals, we are developing machine learning models that incorporate additional demographic and observational variables to improve NEWS2's sensitivity. Our analysis of 9.8 million observations has identified significant opportunities to enhance detection in precisely the populations the original scoring system was not designed around. (Video)
Key finding: Observation-level ML analysis across 9.8 million records demonstrates a 16% improvement in sensitivity (AUROC 0.815 vs 0.777) for predicting clinical deterioration compared to standard NEWS2 scoring.
Relevant publications:
- Modifications to the National Early Warning Score: a scoping review protocol
- Modifications to the National Early Warning Score 2: a scoping review
Autonomous AI Follow-Up for Cataract Surgery (Ufonia/Dora)
Status: Completed
Funder: NIHR AI in Health and Care Award
Collaborator: Ufonia Ltd.
Sites: Two NHS Trusts
Cataract surgery is the most common operation in the UK, yet most trusts still require face-to-face post-operative follow-up despite low complication rates. We co-led an evaluation of Dora, an autonomous conversational AI agent delivered by telephone, assessing whether it could safely and accurately perform post-surgical follow-up and identify patients needing further review. Dora's performance was compared against ophthalmic specialists across two NHS trusts.
Key finding: The study found good preliminary evidence of Dora's safety and accuracy for routine follow-up, with generally positive usability ratings. The results also highlighted the importance of maintaining human involvement for patients with concerns or complications. Published in The Lancet eClinicalMedicine.
Relevant publications:
- Effectiveness of Conversational Agents in Health Care: Protocol for a Systematic Review
- The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review
- Safety and Acceptability of a Natural Language Artificial Intelligence Assistant to Deliver Clinical Follow-up to Cataract Surgery Patients: Proposal
- Accuracy and safety of an autonomous artificial intelligence clinical assistant conducting telemedicine follow-up assessment for cataract surgery