AI in Scheduling for Healthcare – Opportunities, Challenges, and Eliminating Time-Consuming Processes
Session
Computer Science and Communication Engineering
Description
The rapid growth of demand in healthcare has created significant challenges in managing patient appointments effectively. Traditional scheduling methods, often reliant on manual processes, phone calls, and in-person visits, are prone to human error, increased administrative burden, and delays in patient care. With rising patient volumes and limited healthcare staff, the need for intelligent scheduling solutions has become critical to avoid bottlenecks and ensure timely access to care. This thesis examines the integration of Artificial Intelligence (AI) into hospital appointment scheduling to optimize resource allocation, reduce patient waiting times, and improve overall service quality. The proposed AI-driven solution employs natural language processing for voice- and text-based patient interactions, machine learning models to predict appointment availability, and real-time synchronization with hospital information systems. The research adopts a mixed approach, combining literature review and system prototyping to assess both technical feasibility and practical implications. By automating the scheduling process, hospitals can minimize human errors, reduce staff workload, and enhance the patient experience. Furthermore, the study evaluates the opportunities and challenges of AI adoption in healthcare, highlighting its potential not only to increase efficiency but also to transform healthcare delivery through intelligent automation.
Keywords:
Artificial intelligence, Hospital, Appointments, Opportunities, Challenge
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-982-41-2
Location
UBT Kampus, Lipjan
Start Date
25-10-2025 9:00 AM
End Date
26-10-2025 6:00 PM
DOI
10.33107/ubt-ic.2025.79
Recommended Citation
Bytyqi, Erestinë; Hajrizi, Edmond; and Qehaja, Besnik, "AI in Scheduling for Healthcare – Opportunities, Challenges, and Eliminating Time-Consuming Processes" (2025). UBT International Conference. 11.
https://knowledgecenter.ubt-uni.net/conference/2025UBTIC/CS/11
AI in Scheduling for Healthcare – Opportunities, Challenges, and Eliminating Time-Consuming Processes
UBT Kampus, Lipjan
The rapid growth of demand in healthcare has created significant challenges in managing patient appointments effectively. Traditional scheduling methods, often reliant on manual processes, phone calls, and in-person visits, are prone to human error, increased administrative burden, and delays in patient care. With rising patient volumes and limited healthcare staff, the need for intelligent scheduling solutions has become critical to avoid bottlenecks and ensure timely access to care. This thesis examines the integration of Artificial Intelligence (AI) into hospital appointment scheduling to optimize resource allocation, reduce patient waiting times, and improve overall service quality. The proposed AI-driven solution employs natural language processing for voice- and text-based patient interactions, machine learning models to predict appointment availability, and real-time synchronization with hospital information systems. The research adopts a mixed approach, combining literature review and system prototyping to assess both technical feasibility and practical implications. By automating the scheduling process, hospitals can minimize human errors, reduce staff workload, and enhance the patient experience. Furthermore, the study evaluates the opportunities and challenges of AI adoption in healthcare, highlighting its potential not only to increase efficiency but also to transform healthcare delivery through intelligent automation.