AI Clinician XP1
Research type
Research Study
Full title
Passive evaluation in operational environment of the AI Clinician decision support system for sepsis treatment.
IRAS ID
297800
Contact name
Anthony C Gordon
Contact email
Sponsor organisation
Imperial College London
Duration of Study in the UK
1 years, 7 months, 4 days
Research summary
Sepsis, or systemic infection, is a common reason for ICU admission and death throughout the world. Despite advances in the way we treat this condition, it remains a significant economic and healthcare burden. A key part of the treatment of sepsis is the administration of IV fluids and blood pressure medication. However, there is huge uncertainty around dosing of these drugs in an individual patient. A tool to personalise these medications could improve patient survival. We have developed a new method to automatically and continuously review and recommend the correct medication doses to doctors, which was created using artificial intelligence (AI) techniques applied to large medical databases. Our previous work has shown it has the potential to improve patient survival rates. The tool will be capable of processing patient data within the electronic patient record of NHS hospitals in real-time to suggest a course of action. This tool will be evaluated and refined in simulation studies and then be tested in two NHS Trusts in “shadow mode” (results not provided to duty clinicians). This will allow comparison of actual decisions made and recommended decisions from the AI system. The second stage of this clinical evaluation will display the recommendations to clinicians to assess the acceptability of the tool and confirm technical feasibility to inform future clinical trials. The long-term expected benefits of this project are numerous: improved patient survival, reduced use of precious intensive care resources and reduction in healthcare costs. There is much debate around the perceptions of AI in medicine, so we have had strong PPI involvement and these stakeholders will continue to be involved throughout. In order to influence clinical practice, we intend to feedback progress to our sites. Wide dissemination to the scientific community, through peer-reviewed publication, and to the general public is also planned.
REC name
South Central - Hampshire B Research Ethics Committee
REC reference
21/SC/0383
Date of REC Opinion
25 Jan 2022
REC opinion
Further Information Favourable Opinion