The Role of AI in Optimizing Healthcare Appointment Scheduling
AI is the most interesting area of healthcare, which is currently making its way into the medical field. Artificial Intelligence has become a game changer, in the healthcare industry bringing forth solutions to problems. A particular area of focus for AI advancements in years has been appointment scheduling with the aim of improving efficiency and accessibility for patients. To overcome these challenges AI technologies have been utilized to develop scheduling systems that utilize data-driven insights and machine learning algorithms. This paper is to investigate appointment scheduling systems in the healthcare sector. The healthcare sector is a major part of the economy. Through surveys, the appointment scheduling system can improve its efficiency. Artificial Intelligence proposes methods for advancing appointment scheduling, which helps control the scheduling window. It can reduce patient no-shows, manage long waitlists, take rapid action over medical urgency, and enhance the department's use of resources for outpatients. Further, the paper examines the problem of appointment management in the healthcare sector considering the various outcoming problems. This paper overlooks the different components of Artificial Intelligence that are applied to the appointment system. We also observe the challenges in the system and the open issues. The objective is to improve the appointment system in the healthcare sector and regulate it with the advancement of Artificial Intelligence.
Authors
- Atul Agrawal (ORCID: https://orcid.org/0009-0004-3601-3919)
- Sunita Rani (ORCID: https://orcid.org/0000-0001-9001-6425)
- Puneet Garg (ORCID: https://orcid.org/0000-0001-9490-7268)
- M. A. Iqbal (ORCID: https://orcid.org/0000-0001-8664-1949)
- Bhupendra Kumar
- Reeta Parmer
Institutions
- Indian Institute of Technology Roorkee (IN)
- Galgotias University (IN)
- Quantum University
Publication Details
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1109/icdt63985.2025.10986601
- Citations
- 2
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 5.03