Surgical Waiting Times in Turkish Public Hospitals: A Conceptual Framework for an Artificial Intelligence-Driven Mobile Application

Prolonged surgical waiting times in Turkish public hospitals pose significant challenges to patient health, satisfaction, and healthcare system efficiency, driven by rising demand, limited resources, and systemic inefficiencies. This study proposes a conceptual framework for an artificial intelligence (AI)-enabled mobile application to address these issues, leveraging Türkiye’s e-Nabız platform and Hospital Information Management System (HBYS). The system integrates real-time hospital data—such as operating theater occupancy and specialist availability—with machine learning algorithms to predict waiting times, prioritize patients based on clinical urgency, and guide them to facilities with shorter delays. Designed to enhance transparency and optimize resource allocation, the application has the potential to reduce waiting times by an estimated 15–20%, aligning with international benchmarks like the UK’s National Health Service (NHS) and Australian healthcare models (NHS Digital, 2021). By utilizing anonymized data, the system complies with Türkiye’s Personal Data Protection Law (KVKK, 2016), requiring no ethics approval. Benefits include improved patient empowerment, reduced complication risks (estimated at 10–20% due to delays), and enhanced operational efficiency (Siciliani et al., 2014). This framework offers a scalable, patient-centered solution to modernize Türkiye’s public healthcare system, with future pilot studies recommended to validate its impact.