C2-Ai
Using Ai and Machine learning to provide granular risk stratification and prioritisation of the waiting list C2-Ai helps hospitals enhance patient safety, reduce mortality, and minimise clinical outcomes variation by using AI-backed insights. It conducts patient-specific risk assessments integrating factors such as ethnicity and social determinants of health.
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C2-AI enrich the Patient Tracking List by providing validation, risk assessment, and advanced prioritisation, crafting lists that are responsive to each patient’s health needs, in line with hospital protocols and pathways, ensuring governance and evidential standards are met.
C2-Ai utilise existing hospital data to yield quantifiable outcomes, improving patient care, efficiency in operations, and clinical performance, and fulfilling Core20Plus5 objectives.
Designed with a focus on patients, C2-Ai requires no additional infrastructure and can be fully operational in days.
The impact
Direct impact on Patient Tracking List from using C2-Ai:
- 98% clinician acceptance of suggested prioritisation
- 125 bed days released per 1,000 patients
- Switching 2/3rds to non-surgical or safer pathways saved approx. 60% on HDU/ICU utilisation for highest-risk patients
- Refusal of referrals to HVLC low-acuity sites cut from >60% to sub 5%
- Targeting deteriorating patients avoided 8% ED admission from among 20,000 patients
- 27% reduction in >52 week waiters, during 6-week trial
Pre-habilitationand waiting-well case matched trials. Identifying most at-risk patients with COPD achieved:
- 95% reduction in targeted complications
- 56% reduction in all-cause complications
- 4.2 days average reduction in length of stay
- Net Promotor Score of 80
“Our ability to use technology to identify high risk patients ahead of surgery is important. When this is accompanied by an intervention to then optimise them ahead of surgery, it is incredibly powerful.”
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