Fast, evidence-based triage of surgical lists

Applying a proven, published approach that helps prioritise those on the surgical elective list with significant results

Time saved per Assessment

5-15 Minutes

saveD every time EVERY patient
iS assessed

Capacity Impact

125 Bed-days

saveD PER 1,000 PATIENTS

Emergency Admissions

8% Reduction

FROM THOSE ON THE LIST

Surgeon Years Saved with C2-Ai

20,000

(UP TO) ACROSS THE NHS

THE PROBLEM: Manual prioritisation is time consuming, prone to bias and error, and leaves tens of thousands in the same category

Manual prioritisation is time-consuming but still leaves thousands if not tens of thousands of patients in the same priority category. Up to 15% of patients may be in the ‘wrong’ category and there is no mechanism to prioritise them across patients in the different specialties and potentially in different sites.

THE SOLUTION: C2-Ai’s Prioritisation System automatically delivers the detailed clinical risk needed to prioritise complex waiting lists

Professor Rowan Pritchard Jones talks about the impact of C2-Ai’s risk stratification and prioritisation of the elective waiting list

THE IMPACT: Demonstrable improvements – reduction of harm, length of stay, mortality, and emergency admissions

The system integrates into existing pathway management tools and can triage hundreds of thousands of patients a day, processing and reprocessing the waiting list dynamically at scale to deliver (NHS-reported results):

125 bed days saved per 1,000 patients
Up to an 8% reduction in emergency admissions from those on the list.

Lower patient harm and mortality

Better use of surgeon time (currently 15 minutes are spent for every patient review).

A more detailed view of clinical risk for each patient.

Optimisation of sites and routing across trusts and regions to match patient risk (60% rejection in private settings reduced to near 0)
Support to help identify which patient to optimise prior to operation

125 bed days saved per 1,000 patients
Up to an 8% reduction in emergency admissions from those on the list.

Lower patient harm and mortality

Better use of surgeon time (currently 15 minutes are spent for every patient review).

A more detailed view of clinical risk for each patient.

Optimisation of sites and routing across trusts and regions to match patient risk (60% rejection in private settings reduced to near 0)
Support to help identify which patient to optimise prior to operation

C2-Ai has repurposed and automated existing systems that have been in use by the NHS and globally for 15 years, building on 30 years of research and the world’s largest referential patient dataset (over 400 million records from 46 countries through our systems over the years). Our approach (as featured on the BBC in September 2020) prioritises patients based on quantifiable risk and likelihood of deterioration while on the waiting list.

The system scientifically addresses Social Determinants of Health fairly, equitably, and without bias.

Get in touch

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To read the BMJ article on the system

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The system is simple to use, requires no complex integration and has an interface to sort the list, create weekend lists etc.

WAITING WELL, ELECTIVE RECOVERY AND BEYOND: Supporting important initiatives

The system provides critical insights that support improvement and transformation initiatives:

‘Waiting Well” 2.6 day reduction in Length of Stay, 65% reduction in complications, and no chest infections for patients with respiratory issues waiting on the list. Targeting the right patients [C2-AI] combined with health support.
Planning capacity – beds, theatre capacity, theatre light settings (no ICU).
Creation of weekend lists of low-acuity patients