Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2174
Title: BLE-based Real-time Location System Integration with Hospital Information System to Reduce Patient Waiting Time
Authors: Osman M.S. 
Azizan A. 
Hassan K.N. 
Ghani, H.A. 
Hassan N.H. 
Yakub F. 
Daud S.M. 
Latiff L.A. 
Keywords: Bluetooth;Hospitals;Prototypes;Data visualization;System integration;Quality of service;Real-time systems
Issue Date: Jun-2021
Publisher: IEEE
Conference: 3rd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2021 
Abstract: 
Emergency and Trauma department (ETD) in Malaysia's public hospitals receives millions of patients than other clinics due to cheap charges and reliable services, however most of them are Green Zone non-critical patients. Long waiting time for patient treatment results into congestion and affects the quality of service provided in the ETD. To date only 20 public hospitals in Malaysia implements Hospital Information System (HIS) and patient waiting time is captured from the system manually, thus lacking the functionality to track patient in realtime. Despite studies conducted worldwide, studies on design, development and implementation of RTLS in public hospital in Malaysia have not been conducted yet. This paper examines a Bluetooth Low Energy (BLE) based Real-time Location System (RTLS) implementation in ETD with HIS integration to reduce patient waiting time. We develop a Bluetooth Low Energy (BLE) based RTLS prototype that is integrated with existing HIS at ETD, Hospital Putrajaya and augment data visualization interventions to reduce patient waiting time in ETD. Preliminary results show substantial benefits of patient waiting time reduction leading to improvement of service quality. Our preliminary findings show when RTLS is introduced in the ETD workflow, the mean ATC time was significantly reduced to 10.47% in comparison to HIS without RTLS.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/2174
ISBN: 978-166543897-1
DOI: 10.1109/ICECCE52056.2021.9514248
Appears in Collections:Faculty of Data Science and Computing - Proceedings

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