Changing the underlying economics for payors 

Revamping provider networks and referrals to optimize patient outcomes, reduce costs, and save $billions…

Hospitals only see the tip of the iceberg in terms of drivers of cost and quality variation

C2-Ai can help payors evolve their network over time, whether that’s at hospital, specialty, sub-specialty or physician level – removing outliers and driving improvements in others.  These insights can help drive Medicare/Medicaid patients to better margins, and also power a unique approach to intelligent referral management.

Minimizing patient cost while improving outcomes

Deriving overall expected treatment costs based on:
  • procedure/complication costs by site (at specialty/sub-specialty level)
  • complication risk (considering patient risk and site quality)

Enables calculation of the expected patient treatment cost to minimise costs while improving patient outcomes.  This enables 

  • Identification/elimination of sub-optimal choices
  • Automated decision support to promote ‘right’ location for patient referrals 

Slashing cost in the provider network

Right location, right team, right cost
Precision analytics on cost versus real quality in provider network across sites (hospital/ASC etc.)/specialties/sub-specialties/ physicians.
Save billions (USD) by
  • Removing outliers
  • Negotiating harder on rates based on quality
  • Directing patients to better quality provision

Optimized referrals management

Sending the right patient to the right place at the right time
Match individual precision clinical risk to the ‘right’ location
Minimise mortality complications, conversions to inpatient and cost by sending patients to a site that matches their individual clinical risk (specialist hospital, hospital, clinic, Ambulatory Surgery Centre/Surgical Hub)
  • 8% reduction in emergency admissions
  • 125 bed-days saved per 1,000 patients

Unique capabilities performing truly ground-breaking analysis…


more issues detected across hospitals – clearly actionable for in-year ROI

9 × 10⁴⁵³

permutations per patient delivering clincial risk assessment with exceptional accuracy – validated and published


AI-enhanced discrete metrics that matter – uncovering even hidden issues (failures to respond, omissions to treat)

Successfully delivering meaningful outcomes and insights…


Potential direct cost savings per hospital (recurring per annum)


complication metrics for medical patients


Reduction in emergency admissions


years of surgeon time served (NHS at 100% scale)


bed-days saved per 1,000 patients


reduction in Hospital Acquired Pneumonia/AKI

Based on decades of research and extensive hospital data


patient records processed from 46 countries


of research and 15 years of real world deployment across 11 countries


adoption in NHS ICS regions as well as government + regulators + ‘for profit’ hospitals in US 

Recent awards and recognition 


combinations of operative type and physiology


person years of surgeon time could be saved 


Reduction in harm and mortality


weeks of triage time saved per surgeon

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