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ZENODO
Article . 2019
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2019
License: CC BY
Data sources: Datacite
ZENODO
Article . 2019
License: CC BY
Data sources: Datacite
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IMPROVING CLINIC QUEUES IN MALAYSIA USING TIME-SERIES EXTRAPOLATION FORECAST AND WEB-BASED APPOINTMENT

Authors: Bee Bee, Koay; Letchmunan, Sukumar A/L; Marashdih, Abdalla Wasef;

IMPROVING CLINIC QUEUES IN MALAYSIA USING TIME-SERIES EXTRAPOLATION FORECAST AND WEB-BASED APPOINTMENT

Abstract

In University of Science, Malaysia (USM), Sejahtera Centre is the main healthcare centre that provides medical care to the university students, employees and pensioners. Along the years, the increasing demand for these services has led to long queue problems in the clinic. As a result, the clinic becomes congested during peak hours, leaving both patients and healthcare staffs dissatisfied. Apart from Sejahtera Centre, long queue issue has been a common problem in many government outpatient departments across Malaysia. Therefore, this paper proposes a low-cost, user-friendly clinic management system that consists of a web application for clinic staff and a hybrid mobile application for patients. Real-time queue monitoring and queue forecasting using Time-Series Extrapolation is incorporated to help patients avoid peak hours and empower better clinic workforce management in handling different patient flow peaks. The web-based appointment approach allows patients to conveniently reschedule their appointments online and receive appointment reminders via the mobile application. To demonstrate the feasibility and effectiveness of the proposed system, a prototype is developed and evaluated based on several interviews. The prototype serves as a basic working model that outlines the feasibility of the proposed concepts to improve queue issues in other clinics across Malaysia. 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green