AI Speeds Urgent Elective Surgery by 27%

A healthcare organization faced a growing backlog of elective surgeries, leading to longer wait times and increased patient risk. To address this issue, they implemented an AI-powered triage system that enables the prioritization of care and resource allocation. This led to fewer emergency admissions, avoidable surgery cancellations, and faster treatment for high-priority patients.

Client:

The National Health Service (NHS) is a publicly funded healthcare system in England that provides free healthcare to all UK citizens. It is the largest single-payer healthcare system in the world, employing over 1.3 million people.

Problem Statement:

● Inefficient patient prioritization: Traditional methods failed to identify patients at high risk of complications or deterioration, leading to suboptimal resource allocation and potential harm to patients.
● Growing backlog of elective surgeries: The increasing number of patients waiting for elective surgeries put a strain on the NHS’s resources and exacerbated patient wait times.

Results:

NHS Achieves Remarkable Results with AI-Powered Patient Prioritization:
☑️ 98% surgeon agreement with PTL’s prioritization metrics.
☑️ 15-minute time saving per patient during re-prioritization.
☑️ 125 bed-days freed up per 1,000 patients on PTL.
☑️ 8% reduction in emergency admissions.
☑️ 100% reduction in avoidable surgery cancellations.
☑️ 27% reduction in long wait times for high-urgency patients.

AI Solution:

To address the growing backlog of patients requiring elective surgeries, the NHS implemented the Patient Tracking List (PTL), an AI-powered triage system developed by C2-Ai.

This system analyzes patient data, including medical history, social determinants of health, and the type of surgery planned. Using a sophisticated algorithm trained on data from millions of patients across 46 countries, PTL predicts the risk of complications during or after surgery.

By applying PTL, the NHS

● Identifies high-risk patients: The system pinpoints patients most likely to experience complications, allowing surgeons to prioritize their care.
● Optimizes resource allocation: Accurate risk assessments allow surgeons to ensure that resources are directed toward patients who need them most.
● Improves patient outcomes: Early identification of high-risk patients enables proactive measures to minimize complications and potentially improve overall patient outcomes.

This AI solution empowers the NHS to address the backlog of elective surgeries efficiently and effectively, prioritizing patient needs and optimizing resource allocation.

References:

1. AI to prioritize patients waiting for elective surgery

Industry: Healthcare
Vendor: C2-Ai
Client: National Health Service (NHS)