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Clinical Evaluation of an AI Risk Prediction System (AI-TRiPS) (AI-TRiPS)

3 giugno 2026 aggiornato da: Queen Mary University of London

Clinical Evaluation of an AI Risk Prediction and Decision Support System for Early Management of Injured Patients: a Stepped-wedge Cluster Randomised Trial

The goal of this clinical study is to evaluate a software device and its impact on clinician behaviour during the initial management of trauma patients in a real-world clinical setting. Known as the AI-TRiPS Device this software uses real-time prehospital data and machine learning-based risk predictions which are displayed digitally for hospital trauma teams prior patient arrival.

The investigators will use a Stepped Wedge Cluster Randomised Controlled study design with an integrated process evaluation.

The Device will be deployed across the London Major Trauma System where the Major Trauma Centres will be the clusters. Each cluster will transition from control (standard care) to intervention at a pre-specified time (time of transition is randomised).

Primary Outcome: Clinician behaviour, assessed via the accuracy of risk prediction and clinician confidence.

Secondary Outcome: Clinician acceptability, care process metrics, patient outcomes, and safety endpoints.

Primary study population: Hospital trauma clinicians, following initial resuscitation of each eligible trauma patient, who will complete electronic questionnaires.

Secondary study population: Adult trauma patients, data will be collected for the duration of their index admission to hospital, to assess outcomes and enable comparison with clinician risk predictions.

Panoramica dello studio

Stato

Non ancora reclutamento

Condizioni

Intervento / Trattamento

Descrizione dettagliata

This project evaluates a bespoke risk prediction system developed by trauma surgeons, pre-hospital clinicians, and computer scientists. The device aims to enhance the situational awareness of hospital trauma teams via a digital display, located in the resuscitation suite, depicting pre-hospital patient status and individualised risk predictions.

Evidence Base and Prior Work

The AI-TRiPS Device builds on an extensive, multi-phase programme of research led by the Centre for Trauma Sciences at Queen Mary University of London, funded by the US Department of Defense, UK Ministry of Defence, and Rosetrees Trust. This programme has:

  • Investigated trauma clinical decision-making, demonstrating that situational awareness is often impaired by uncertainty and cognitive load, and highlighting the need for decision support during early trauma resuscitation.
  • Developed clinically relevant, explainable Bayesian network models using hybrid data- and knowledge-driven methods, with internal and external validation across large civilian and military trauma datasets.
  • Designed and iteratively refined a web-based clinical decision support system (CDSS) to deliver model outputs through an interface tailored to trauma resuscitation workflows, incorporating end-user feedback.
  • Conducted simulation and operational studies demonstrating improved clinician performance with the CDSS compared to unaided judgement.
  • Contributed methodological work to support the safe and effective translation of prediction algorithms into usable and trustworthy clinical tools, including published frameworks for usability testing, implementation evaluation, and explainability in clinical decision support.

The current stage of development is consistent with early-stage clinical evaluation of a Software as a Medical Device (SaMD) under UK MDR 2002 and ISO 14155.

This trial is designed to evaluate clinical performance and safety in real-world conditions, with a primary focus on effects on clinician behaviour and decision-making. While patient outcomes will be collected, the study is not powered to assess downstream impact on clinical outcomes.

Primary Objective To evaluate the impact of the AI-TRiPS device on clinician behaviour during the initial management of trauma patients in a real-world clinical setting, specifically situational awareness (clinician perception of individual patient risk), associated confidence, and cognitive load, compared with standard unassisted clinician performance.

Hypothesis The investigators hypothesise that delivering accurate, real-time risk estimates to trauma clinicians during the initial phase of trauma care will improve situational awareness - in particular, clinicians' perception of individual patient risks - along with increased confidence and reduced cognitive effort, compared with standard unassisted clinician performance.

Null Hypothesis There is no difference in clinician situational awareness (including perception of risk), confidence, or cognitive load between AI-assisted and unassisted clinician performance during initial trauma care.

Secondary objective(s)

Secondary Objectives

• Evaluate impact on Clinician Decision-Making: To assess the effect of the AI-TRiPS device on clinician decision-making, as a potential downstream effect of changes in clinician risk perception (situational awareness).

• Evaluate impact on Clinical Processes: To assess the effect of the AI-TRiPS device on early trauma care processes, including time to critical interventions and length of stay

• Evaluate Patient Impact: To examine patient outcomes associated with clinician exposure to the AI-TRiPS device, recognising these as indirect effects mediated by altered clinical decision-making.

• Evaluate Real-World System Performance: To assess the real-world performance of the AI-TRiPS device, including prediction calibration and the identification of system errors or underperformance that may affect clinical decision-making.

• Evaluate usability and acceptability (Integrated Process Evaluation): To explore the acceptability, usability, and contextual factors that influence the implementation and adoption of the AI-TRiPS device in real-world clinical settings.

Tipo di studio

Interventistico

Iscrizione (Stimato)

1200

Fase

  • Prima fase 1

Contatti e Sedi

Questa sezione fornisce i recapiti di coloro che conducono lo studio e informazioni su dove viene condotto lo studio.

Contatto studio

Backup dei contatti dello studio

Criteri di partecipazione

I ricercatori cercano persone che corrispondano a una certa descrizione, chiamata criteri di ammissibilità. Alcuni esempi di questi criteri sono le condizioni generali di salute di una persona o trattamenti precedenti.

Criteri di ammissibilità

Età idonea allo studio

  • Bambino
  • Adulto
  • Adulto più anziano

Accetta volontari sani

No

Descrizione

Inclusion Criteria:

Clinician Participants

  • Senior clinical decision-maker involved in the initial trauma resuscitation (e.g. consultant or senior trainee in emergency medicine, anaesthesia, intensive care medicine, or surgery).
  • Based at one of the four participating Major Trauma Centres.
  • Able and willing to provide informed consent.
  • Completed the required study-specific training.

Trauma Patients

  • Aged 16 years and above.
  • Treated and transported to a participating Major Trauma Centre by London's Air Ambulance.
  • Managed by one or more participating trauma clinicians during the resuscitation.

Exclusion Criteria:

Clinician Participants

● Decline or withdraw informed consent at any stage.

Trauma Patients

  • Aged under 16
  • Not treated by London's Air Ambulance.
  • Transported to a non-participating hospital.
  • Not managed by any participating clinicians.
  • Presenting with injuries resulting from burns, hangings, drownings, or isolated psychiatric emergencies.
  • Have registered a national NHS data opt-out or otherwise requested that their routine clinical data not be used for research.

Piano di studio

Questa sezione fornisce i dettagli del piano di studio, compreso il modo in cui lo studio è progettato e ciò che lo studio sta misurando.

Come è strutturato lo studio?

Dettagli di progettazione

  • Scopo principale: Altro
  • Assegnazione: Randomizzato
  • Modello interventistico: Assegnazione sequenziale
  • Mascheramento: Nessuno (etichetta aperta)

Armi e interventi

Gruppo di partecipanti / Arm
Intervento / Trattamento
Sperimentale: AI TRIPS device intervention
Patients who fit the eligibility criteria are triaged and treated at the participating trauma centre by trauma clinicians who have been exposed to the individualised risk predictions for that patient.
Dispositivo: AI-TRiPS Device
This is Software as a Medical Device designed to function as an aid to inform clinical situational awareness by presenting predictions of patient trajectory (probability of death, probability of trauma induced coagulopathy, probability of red cell transfusion, probability of acute kidney injury).
Nessun intervento: Usual Standard Care
Patients who fit the eligibility criteria are triaged and treated at the participating trauma centre by trauma clinicians under standard conditions.

Cosa sta misurando lo studio?

Misure di risultato primarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Clinician Risk Prediction - Mortality, Trauma Induced Coagulopathy, and Acute Kidney Injury
Lasso di tempo: Baseline
Clinician participants will make probability estimates (0-100%) on index admission in each of the 3 domains.
Baseline
Clinician Risk Prediction - Estimation of Blood Transfusion Volume
Lasso di tempo: Baseline
Clinicians will estimate the number(n) of packed red blood cell (pRBC) units required for transfusion in the first 24 hours. The estimation will take place immediately after initial resuscitation.
Baseline
Clinician Confidence
Lasso di tempo: Baseline to 24 Hours - Immediately following initial clinician predictions
Clinician Participants will self-report their confidence in their predictions using the Post-Task Confidence Scale (PTCS), a Likert scale from 1-7, where the higher the score the higher the level confidence.
Baseline to 24 Hours - Immediately following initial clinician predictions
Clinician Cognitive Effort
Lasso di tempo: Baseline to 24 Hours - immediately following risk predictions
Clinician participants self-report the mental effort required to make each prediction using the Paas Mental Effort Scale ( Likert Scale 1-9) where a lower score corresponds to low mental effort.
Baseline to 24 Hours - immediately following risk predictions
Risk Prediction Accuracy
Lasso di tempo: From Discharge through to study completion, an average of 1 year.
For each of the 4 domains in which predictions have been made, accuracy of these predictions will be determined with a comparison to patient outcomes. This will be done using the Brier score, however other metrics of predictive performance may also be used to perform comparisons, including measures of discrimination, calibration, and accuracy (Brier skill Score, Mean Absolute Error)
From Discharge through to study completion, an average of 1 year.

Misure di risultato secondarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Clinician Decision-Making Behaviour - Decision Making
Lasso di tempo: From discharge through to study completion, an average of 1 year.

Measurement of whether a decision was made (Decision in this case refers to activation of the major haemorrhage protocol, or proceeding directly to definitive haemorrhage control). This data will be extracted from the National Major Trauma Registry and/or patient clinical records.

Binary (yes/no) based on whether the outcome was performed.
From discharge through to study completion, an average of 1 year.
Clinician Decision-Making Behaviour - Appropriateness of Decision Making
Lasso di tempo: From Discharge through to study completion, an average of 1 year.

Expert panel review of decision making with regards to activation of major haemorrhage protocol/proceeding directly to definitive haemorrhage control. Expert review of extracted patient data from National Major Trauma Registry and/or Patient clinical records.

Binary (Appropriate/Inappropriate)
From Discharge through to study completion, an average of 1 year.
Clinician Decision-Making Behaviour - Clinician Confidence
Lasso di tempo: Baseline to 24 hours - Immediately following initial clinician decision making
Clinician Participants will self-report their confidence in their predictions using the Post-Task Confidence Scale (PTCS), a Likert scale from 1-7, where the higher the score the higher the level confidence.
Baseline to 24 hours - Immediately following initial clinician decision making
Clinician Decision-Making Behaviour - Clinician Cognitive Effort
Lasso di tempo: Baseline to 24 Hours - immediately following risk predictions
Clinician participants self-report the mental effort required to make each prediction using the Paas Mental Effort Scale ( Likert Scale 1-9) where a lower score corresponds to low mental effort.
Baseline to 24 Hours - immediately following risk predictions
Clinician Decision-Making Behaviour - Time Pressure
Lasso di tempo: Baseline to 24 Hours - immediately following decision making
Clinicians self report time pressure using the NASA Task Load Index Temporal Demand Subscale (Likert Scale 1-10). This is measured immediately after each decision.
Baseline to 24 Hours - immediately following decision making
Clinical Process Measures - Time to Major Haemorrhage Protocol(MHP) Activation
Lasso di tempo: Baseline - 12 Hours

Time to MHP activation in minutes(continuous) from arrival to activation of major haemorrhage protocol.

Data collected from National Major Trauma Registry and/or patient hospital records.
Baseline - 12 Hours
Clinical Process Measures - Time to Haemorrhage Control
Lasso di tempo: Baseline - 12 Hours

Time to Haemorrhage control in minutes(continuous) from arrival to start of first definitive haemorrhage control intervention.

Data collected from National Major Trauma Registry and/or patient hospital records.
Baseline - 12 Hours
Clinical Process Measures - Length of Hospital Stay
Lasso di tempo: Discharge through to study completion, an average of 1 year
Total number of inpatient hospital days (continuous), measured from index admission to discharge. Data obtained from National Major Trauma Registry and/or patient clinical records following discharge.
Discharge through to study completion, an average of 1 year
Clinical Process Measures - Intensive Care Unit (ICU) length of stay
Lasso di tempo: Discharge through to study completion, an average of 1 year
Total number of intensive care unit days (continuous), measured from index admission to discharge. Data obtained from National Major Trauma Registry and/or patient clinical records following discharge.
Discharge through to study completion, an average of 1 year
Patient Outcome Measure - In Hospital Mortality
Lasso di tempo: From Baseline to Discharge/Death
Patient death during index hospital admission, Binary (yes/No).
From Baseline to Discharge/Death
Patient Outcome Measure - Trauma Induced Coagulopathy
Lasso di tempo: Baseline
Trauma-induced coagulopathy will be assessed using the admission prothrombin time ratio (PTr). This variable will be recorded as binary (yes/no), with trauma-induced coagulopathy defined as a PTr > 1.2
Baseline
Patient Outcome Measure - Blood Transfusion Volume
Lasso di tempo: Baseline to 24 hours
The total number (N) of units of packed red blood cells (pRBC) transfused to the patient within the first 24 hours post injury.
Baseline to 24 hours
Patient Outcome Measure - Acute Kidney Injury
Lasso di tempo: Baseline to 72 hours
The degree of acute kidney injury will be recorded using the Kidney Disease Improving Global Outcomes(KDIGO) stage 1-3, over the first 72 hours post injury.
Baseline to 72 hours

Collaboratori e investigatori

Qui è dove troverai le persone e le organizzazioni coinvolte in questo studio.

Sponsor

Queen Mary University of London

Collaboratori

King's College Hospital NHS Trust
Barts & The London NHS Trust
Imperial College Healthcare NHS Trust
Congressionally Directed Medical Research Programs
St George's University Hospitals NHS Foundation Trust
University of Aberdeen
London Ambulance Service NHS Trust
London's Air Ambulance Charity

Investigatori

  • Investigatore principale: Prof. N Tai, Queen Mary University London

Pubblicazioni e link utili

La persona responsabile dell'inserimento delle informazioni sullo studio fornisce volontariamente queste pubblicazioni. Questi possono riguardare qualsiasi cosa relativa allo studio.

Pubblicazioni generali

Studiare le date dei record

Queste date tengono traccia dell'avanzamento della registrazione dello studio e dell'invio dei risultati di sintesi a ClinicalTrials.gov. I record degli studi e i risultati riportati vengono esaminati dalla National Library of Medicine (NLM) per assicurarsi che soddisfino specifici standard di controllo della qualità prima di essere pubblicati sul sito Web pubblico.

Studia le date principali

Inizio studio (Stimato)

1 giugno 2026

Completamento primario (Stimato)

1 giugno 2027

Completamento dello studio (Stimato)

1 dicembre 2027

Date di iscrizione allo studio

Primo inviato

6 maggio 2026

Primo inviato che soddisfa i criteri di controllo qualità

3 giugno 2026

Primo Inserito (Effettivo)

8 giugno 2026

Aggiornamenti dei record di studio

Ultimo aggiornamento pubblicato (Effettivo)

8 giugno 2026

Ultimo aggiornamento inviato che soddisfa i criteri QC

3 giugno 2026

Ultimo verificato

1 giugno 2026

Maggiori informazioni

Termini relativi a questo studio

Parole chiave

Termini MeSH pertinenti aggiuntivi

Altri numeri di identificazione dello studio

  • 354225
  • 179821 (Altro identificatore: Queen Mary University)

Piano per i dati dei singoli partecipanti (IPD)

Hai intenzione di condividere i dati dei singoli partecipanti (IPD)?

NO

Informazioni su farmaci e dispositivi, documenti di studio

Studia un prodotto farmaceutico regolamentato dalla FDA degli Stati Uniti

No

Studia un dispositivo regolamentato dalla FDA degli Stati Uniti

No

Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .

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