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http://dx.doi.org/10.6109/jkiice.2018.22.4.575

A System Design for Real-Time Monitoring of Patient Waiting Time based on Open-Source Platform  

Ryu, Wooseok (Department of Healthcare Management, Catholic University of Pusan)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.22, no.4, 2018 , pp. 575-580 More about this Journal
Abstract
This paper discusses system for real-time monitoring of patient waiting time in hospitals based on open-source platform. It is necessary to make use of open-source projects to develop a high-performance stream processing system, which analyzes and processes stream data in real time, with less cost. The Hadoop ecosystem is a well-known big data processing platform consisting of numerous open-source subprojects. This paper first defines several requirements for the monitoring system, and selects a few projects from the Hadoop ecosystem that are suited to meet the requirements. Then, the paper proposes system architecture and a detailed module design using Apache Spark, Apache Kafka, and so on. The proposed system can reduce development costs by using open-source projects and by acquiring data from legacy hospital information system. High-performance and fault-tolerance of the system can also be achieved through distributed processing.
Keywords
Big Data; Open-Source; Patient Waiting Time; Spark;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 S. I. Park, and K. B. Kim, "Analysis of The Delayed Time in Patients with Acute Appendicitis," in Proceedings of the Korean Institute of Information and Communication Sciences, pp. 889-892, 2013.
2 K. Ganesha, S. Dhanush, and S. M. S. Raj, "An approach to fuzzy process mining to reduce patient waiting time in a hospital," in Innovations in Information, Embedded and Communication Systems (ICIIECS), pp. 1-6, 2017.
3 A. Baldominos, F. D. Rada, Y. Saez, "DataCare: Big Data Analytics Solution for Intelligent Healthcare Management," International Journal of Interactive Multimedia and Artificial Intelligence, vol. 4, no. 7, pp. 13-20, 2018   DOI
4 M. Zaharia, et al. "Apache spark: a unified engine for big data processing," Communications of the ACM, vol. 59, no.11, pp. 56-65, Nov. 2016.
5 Apache Kafka [Internet]. Available: http://kafka.apache.org.
6 A distributed database for large datasets [Internet]. Available: http://hbase.apache.org.
7 J. C. Lee, and M. H. Lee, "Big data-based information recommendation system," Journal of the Korea Institute of Information and Communication Engineering, vol. 22, no. 3, pp. 443-450, Mar. 2018.   DOI
8 I. M. Datuk, et al. "Hospital waiting time: the forgotten premise of healthcare service delivery?," International Journal of Health Care Quality Assurance, vol. 24, no. 7, pp. 506-522, 2011.   DOI
9 S. Ha, S. Lee, and K. Lee, "Development of Reference Architecture Based on Big Data Ecosystem," Journal of Security Engineering, vol. 11, no. 6, pp.511-522, Dec. 2014.   DOI
10 Apache Hadoop Official Homepage [Internet]. Available: http://hadoop.apache.org.
11 H. Y. Jung, J. W. Park, and Y. K. Lee, "A Context-Aware Treatment Guidance System," Journal of The Korea Society of Computer and Information, vol. 19, no. 1, pp. 141-147, Jan. 2014.   DOI
12 C. S. Park, and S. H. Koh, "A Case Study on the Improvement of General Hospital Outpatients Waiting Time using TOC Methodology," Korea Journal of Hospital Management, vol. 16, no. 1, pp. 77-100, Mar. 2011.