Discrete Event Simulation and Data Envelopment Analysis Models for Selecting the Best Resource Allocation Alternative at an Emergency Department’s Green Zone

Abstract

(EDHUSM) which provides treatment for non-critical cases contributes partly to the hustle and bustle in the emergency department. The imbalance of doctors and nurses with the patient ratio which forms the resources' bottleneck further results to the long patients' waiting time especially after the office hours and during weekends and public holidays. Collectively, this disproportion and bottlenecks roots up the current problem faced by Green Zone EDHUSM which constantly fails to achieve the KPIs set by the hospital. Henceforth, this study focuses on the best resource allocation of doctors and nurses for shifts during the weekdays and for shifts during weekends and public holidays. The hybrid method of Discrete Event Simulation, and Data Envelopment Analysis models such as BCC-input oriented and Super-Efficiency, were deployed to obtain the best resource allocation for the two groups of shift. The method produced a series of resources allocation alternatives for doctors and nurses with a total of 64 alternatives for weekdays and 729 alternatives for weekends and public holidays. The results show that the best allocation for doctors and nurses during weekdays are three doctors and three nurses serving for every shift, while during weekends and public holidays, a combination of four doctors and four nurses for every shift are the best. The proposed combinations have reduced the average waiting time, optimized the utilization of doctors and nurses, and managed to increase the number of patients served during weekdays, weekends and public holidays.

The Application of Data Envelopment Analysis to Emergency Departments and Management of Emergency Conditions: A Narrative Review

“…The gap between the number of doctors and nurses and the patient ratio creates a bottleneck in the available resources, leading to long waiting times for patients, particularly after office hours, and during weekends. To achieve the optimal resource allocation for the two shift groups, a combination of DES integrated with BCC input-oriented and super-efficiency methods was proposed by Yusoff et al [ 84 ]. This approach generated multiple resource allocation options for doctors and nurses, amounting to 64 options available for weekdays and 729 options available for weekends.…”

Research Trends in the Optimization of the Master Surgery Scheduling Problem

“…Adan et al [21] noted that a master plan brings a more balanced utilization of beds, OTs and nursing staff. Balanced resource utilization is critical because surgeons and nurses may be unable to take appropriate rest if they are overutilized [22]. Sufficient breaks are essential in ensuring that hospital staff can provide high-quality medical care to patients [23].…”

“…Besides, one of the most significant OT planning and scheduling issues is uncertainty [3]. OT planning and scheduling may include stochastic variables (stochastic approach) or neglects them (deterministic approach) [22]. The types of uncertainty identified are duration, arrival, resource and care requirement [5].…”

Model Sistem Dinamik untuk Meramalkan Bilangan Pesakit dan Keperluan Sumber Tenaga di Zon Kuning Jabatan Kecemasan

“…Secara tidak langsung, ia bertepatan dengan hasil yang diperoleh oleh Mohd et al (2016) dalam kajian beliau yang menyatakan perlu penambahan seramai empat orang doktor bagi menambahbaik aliran pesakit dan mengurangkan masa menunggu pesakit di Zon Kuning Pusat Perubatan Universiti Malaya (PPUM). Selain itu, hasil kajian ini juga turut menyokong hujah Aminuddin et al (2016), Norazura et al (2014Norazura et al ( , 2013, Yusoff et al (2018bYusoff et al ( , 2017 bahawa perlunya penambahan bilangan sumber seperti bilangan doktor, jururawat dan katil bagi menambahbaik operasi perkhidmatan dan aliran pesakit di jabatan kecemasan. Sebarang penambahbaikan yang dilakukan akan mendorong kepada pengurangan tempoh masa menunggu pesakit yang lama, kesesakan dan ketidakpuasan pesakit terhadap perkhidmatan di hospital (Azaiez & Al-Sharif 2005;Jeenanunta et al 2013;Yusoff et al 2018bYusoff et al , 2017.…”

“…Selain itu, hasil kajian ini juga turut menyokong hujah Aminuddin et al (2016), Norazura et al (2014Norazura et al ( , 2013, Yusoff et al (2018bYusoff et al ( , 2017 bahawa perlunya penambahan bilangan sumber seperti bilangan doktor, jururawat dan katil bagi menambahbaik operasi perkhidmatan dan aliran pesakit di jabatan kecemasan. Sebarang penambahbaikan yang dilakukan akan mendorong kepada pengurangan tempoh masa menunggu pesakit yang lama, kesesakan dan ketidakpuasan pesakit terhadap perkhidmatan di hospital (Azaiez & Al-Sharif 2005;Jeenanunta et al 2013;Yusoff et al 2018bYusoff et al , 2017. Justeru, peramalan sumber yang dihasilkan oleh model simulasi SD Zon Kuning yang dibangunkan mampu mendapatkan hasil bilangan sumber yang diperlukan bagi memenuhi permintaan pesakit yang berkunjung pada masa kini dan akan datang.…”