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An optimized queue management system to improve patient flow in the absence of appointment system
Komal Aqeel Safdar1, Ali Emrouznejad2, Prasanta Kumar Dey3
1Khalifa University, Abu Dhabi, UAE.
Purpose:
The aim of this research study is to develop a queue assessment model to evaluate the inflow of walk-in outpatients in a busy public hospital of an emerging economy, in the absence of appointment systems, and construct a dynamic framework dedicated towards the practical implementation of the proposed model, for continuous monitoring of the queue system.
Design/Methodology/Approach:
The current study utilizes data envelopment analysis (DEA) to develop a combined queuing-DEA model as applied to evaluate the wait times of patients, within different stages of the outpatients' department at the Combined Military Hospital (CMH) in Lahore, Pakistan, over a period of seven weeks (23rd April to 28th May 2014). The number of doctors/personnel and consultation time were considered as outputs, where consultation time was the non-discretionary output. The two inputs were wait time and length of queue. Additionally, VBA programming in Excel has been utilized to develop the dynamic framework for continuous queue monitoring.
Findings:
The inadequate availability of personnel was observed as the critical issue for long wait times, along with overcrowding and variable arrival pattern of walk-in patients. The DEA model displayed the "required" number of personnel, corresponding to different wait times, indicating queue build-up.
Originality/Value:
The current study develops a queue evaluation model for a busy outpatients' department in a public hospital, where "all" patients are walk-in and no appointment systems. This model provides vital information in the form of "required" number of personnel which allows the administrators to control the queue pre-emptively minimizing wait times, with optimal yet dynamic staff allocation. Additionally, the dynamic framework specifically targets practical implementation in resource-poor public hospitals of emerging economies for continuous queue monitoring.
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