Transforming ENT Surgical Triage: A Novel AI-Driven Approach to Chronic Sinusitis Management

Mar 19, 2024 | by Brad Bichey


Objective: This study aims to address the inefficiencies in traditional pathways for chronic sinusitis management assessing an Artificial Intelligence (AI) and Machine Learning (ML) based business process used in surgical triage, enhancing patient care.

Data Sources: Data from a novel Software as a Service (SaaS) solution, utilizing AI algorithms and multimodal communication, including SMS, to optimize the surgical care pathway for chronic sinusitis patients.

Review Methods: The study analyzes over 10,000 patient journeys through a software system, focusing on the implementation and impact of the AI-enhanced triage system.

Conclusions: The SaaS solution featured AI-enhanced algorithms for personalized scheduling, statistical analysis, and a patent-pending multimodal communication system. This approach aimed to streamline the triage process, reduce wait times, and improve overall efficiency and patient satisfaction in surgical care. Results indicated the AI-driven triage pathway identified 55% of patients as suitable surgery candidates, and reduced time to treat significantly. SMS communication increased patient engagement by 65%, aiding implementation of a ‘Surgical Stacking’ approach. This approach successfully prequalified surgical candidates and enhanced resource utilization, showing a 50% improvement in cost and efficiency. Additionally, 90% of patients met prior authorization criteria, significantly reducing the need for peer-to-peer interactions.

Implications for Practice: The introduction of an AI-enhanced triage system markedly improves the management of chronic sinusitis, demonstrating significant advancements in patient scheduling and prequalification. This approach optimizes efficient, patient-centric surgical care and indicates the potential for broader AI integration in healthcare, offering solutions to overcome language barriers and applicability across other specialties.

Keywords: Artificial Intelligence, Machine Learning, Chronic Sinusitis, Surgical Triage, Healthcare Efficiency, Software as a Service (SaaS), Patient Engagement.