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Smart Appointment Scheduling to Reduce Hospital Wait Times
Subject area: Science,Engineering and Technology · Area of research: Digital Healthcare Systems
DOI: https://doi.org/10.64388/IREV9I11-1717931
Abstract
The healthcare sector in Karnataka and Tamil Nadu is rapidly advancing, but many medium-scale hospitals still depend on manual administrative processes such as physical registers and token-based queues. Increasing patient numbers and outdated workflows create delays in registration, overcrowding, and difficulties in managing medical records. Existing hospital management systems are often fragmented, where appointment booking systems do not synchronize with doctor availability or patient history [9]. As a result, multiple patients are scheduled at the same time, causing long waiting periods and stress for both patients and hospital staff. In addition, paper-based medical records increase the risk of file misplacement and data leakage. The major research gap lies in the lack of integration between intelligent scheduling systems and secure digital record management. Most studies focus only on queue optimization [10] or data security [5] separately rather than combining both into a unified healthcare solution. To address this issue, this research proposes a Smart Resource Aware Scheduling (SRAS) framework. The system uses historical consultation data and real-time doctor activity to create flexible appointment scheduling. If delays occur, the system automatically updates appointment timings and sends notifications to patients [7]. At the same time, a centralized encrypted digital repository securely stores and retrieves patient records during check-in, supporting a paperless hospital environment [4]. The proposed framework is expected to reduce hospital overcrowding, improve appointment efficiency, and minimize medical record loss. This study provides a scalable solution for the digital transformation of regional healthcare centers in Southern India.
Keywords
Smart Appointment Scheduling, Healthcare Digitalization, Smart Scheduling, Hospital Wait Time (HWT), Electronic Health Records (EHR), Outpatient Department (OPD) Optimization, Resource Aware Scheduling
References
[1] Z. Zhang, et al., "Smart Medical Appointment Scheduling: Optimization, Machine Learning, and Overbooking to Enhance Resource Utilization," IEEE Access, vol. 12, pp. 33499-33512, Jan. 2024. [Focus: ML for predicting no-shows].
[2] M. S. Kumar and R. Jayanthi, "Reducing Waiting Times to Improve Patient
[3] Satisfaction: A Hybrid Strategy for Decision Support Management," MDPI Mathematics, vol. 12, no. 23, 3743, Dec. 2024. [Focus: Hybrid models for hospital bottlenecks].
[4] S. Smith, et al., "The Impact of Digital Hospitals on Clinician and Patient Experiences: A Systematic Review," Journal of Medical Systems (Springer), vol. 48, no. 2, pp. 102-115, 2024. [Focus: Paperless management benefits.
[5] L. Huang and F. Guo, "IoT-Cloud Data Sharing and Access Control System with Efficient Policy Updating," IEEE Transactions on Cloud Computing, vol. 14, no. 1, 2026. [Focus: Secure medical record storage].
[6] R. Al-Kahtani and M. Alshahrani, "Impact of Hospital Information Systems (HIS) in Improving Patient Care Quality," International Journal of Digital Health, vol. 3, no. 4, pp. 45-58, 2023. [Focus: Reducing medical errors via digitalization].
[7] J. Kim, et al., "Intelligent Hospital Information Chatbots: Integrating Mobile Notifications with Patient Registration," JMIR Medical Informatics, vol. 13, e77297, 2025. [Focus: Real-time patient alerts].
[8] A. Patil, et al., "Hospital Online Appointment System: A Web-Based Application for Efficient Healthcare Scheduling," International Journal of Engineering Development and Research, vol. 13, no. 2, 2025. [Focus: Reducing physical presence for registration].
[9] C. Bain, "Developing Effective Hospital Management Information Systems: A Technology Ecosystem Perspective," Health Informatics Journal, vol. 30, no. 1, 2024. [Focus: Internal and external factors in hospital decision-making].
[10] H. Liu, et al., "Predicting Waiting Times for Medical Tasks in a Paediatric Hospital Using Machine Learning," Journal of Healthcare Engineering, vol. 2025, ID 88311, 2025. [Focus: Queue theory vs. ML prediction accuracy
How to cite this paper
@article{1717931,
author = {R. Raghavendra, S. Harish Ragaventhiran},
title = {Smart Appointment Scheduling to Reduce Hospital Wait Times},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {11},
pages = {2475-2481},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1717931.pdf},
abstract = {The healthcare sector in Karnataka and Tamil Nadu is rapidly advancing, but many medium-scale hospitals still depend on manual administrative processes such as physical registers and token-based queues. Increasing patient numbers and outdated workflows create delays in registration, overcrowding, and difficulties in managing medical records. Existing hospital management systems are often fragmented, where appointment booking systems do not synchronize with doctor availability or patient history [9]. As a result, multiple patients are scheduled at the same time, causing long waiting periods and stress for both patients and hospital staff. In addition, paper-based medical records increase the risk of file misplacement and data leakage. The major research gap lies in the lack of integration between intelligent scheduling systems and secure digital record management. Most studies focus only on queue optimization [10] or data security [5] separately rather than combining both into a unified healthcare solution. To address this issue, this research proposes a Smart Resource Aware Scheduling (SRAS) framework. The system uses historical consultation data and real-time doctor activity to create flexible appointment scheduling. If delays occur, the system automatically updates appointment timings and sends notifications to patients [7]. At the same time, a centralized encrypted digital repository securely stores and retrieves patient records during check-in, supporting a paperless hospital environment [4]. The proposed framework is expected to reduce hospital overcrowding, improve appointment efficiency, and minimize medical record loss. This study provides a scalable solution for the digital transformation of regional healthcare centers in Southern India.},
keywords = {Smart Appointment Scheduling, Healthcare Digitalization, Smart Scheduling, Hospital Wait Time (HWT), Electronic Health Records (EHR), Outpatient Department (OPD) Optimization, Resource Aware Scheduling},
month = {May},
doi = {https://doi.org/10.64388/IREV9I11-1717931}
}