Estimating optimal resource capacities in emergency department

Ibrahim, Ireen Munira; Liong, Choong Yeun; Bakar, Sakhinah Abu; Ahmad, Norazura; Najmuddin, Ahmad Farid

doi:10.5958/0976-5506.2018.01670.4

Cited by 5 publications

(4 citation statements)

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“…For instance, Al-Assadi and Hasson utilized DES to maximize patients' throughput, minimize waiting times and optimize resources in Hilla ED [35]. A similar study was undertaken by Ibrahim et al who developed a computer simulation model in Arena software to test the response of an ED when facing increased levels of demand [36]. Another work is presented by Nuñez-Perez et al who applied DES to model an Accident & Emergency department [37].…”

Section: Emergency Care Network: Related Studiesmentioning

confidence: 99%

An integrated approach for designing in-time and economically sustainable emergency care networks: A case study in the public sector

Ortíz‐Barrios¹,

Alfaro-Saiz²

2020

PLoS ONE

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Emergency Care Networks (ECNs) were created as a response to the increased demand for emergency services and the ever-increasing waiting times experienced by patients in emergency rooms. In this sense, ECNs are called to provide a rapid diagnosis and early intervention so that poor patient outcomes, patient dissatisfaction, and cost overruns can be avoided. Nevertheless, ECNs, as nodal systems, are often inefficient due to the lack of coordination between emergency departments (EDs) and the presence of non-value added activities within each ED. This situation is even more complex in the public healthcare sector of low-income countries where emergency care is provided under constraint resources and limited innovation. Notwithstanding the tremendous efforts made by healthcare clusters and government agencies to tackle this problem, most of ECNs do not yet provide nimble and efficient care to patients. Additionally, little progress has been evidenced regarding the creation of methodological approaches that assist policymakers in solving this problem. In an attempt to address these shortcomings, this paper presents a three-phase methodology based on Discrete-event simulation, payment collateral models, and lean six sigma to support the design of in-time and economically sustainable ECNs. The proposed approach is validated in a public ECN consisting of 2 hospitals and 8 POCs (Point of Care). The results of this study evidenced that the average waiting time in an ECN can be substantially diminished by optimizing the cooperation flows between EDs.

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Section: Emergency Care Network: Related Studiesmentioning

confidence: 99%

An integrated approach for designing in-time and economically sustainable emergency care networks: A case study in the public sector

Ortíz‐Barrios¹,

Alfaro-Saiz²

2020

PLoS ONE

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“…Fruggiero et al [22] uses ant-colony optimization along with a simulation model to optimize the resources in an emergency department. Weng et al [59], Ibrahim et al [33] and Rico et al [51] use OptQuest, a SO engine [49], to optimize nurse and physician numbers and nurse allocation in an influenza outbreak, respectively. Ghanes et al [23] also uses SO to find the staffing levels in A&E with the objective of minimizing the patient length of stay.…”

Section: Accident and Emergency Modellingmentioning

confidence: 99%

Robust capacity planning for accident and emergency services

Gokalp

2020

RAIRO-Oper. Res.

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Accident and emergency departments (A&E) are the first place of contact for urgent and complex patients. These departments are subject to uncertainties due to the unplanned patient arrivals. After arrival to an A&E, patients are categorized by a triage nurse based on the urgency. The performance of an A&E is measured based on the number of patients waiting for more than a certain time to be treated. Due to the uncertainties affecting the patient flow, finding the optimum staff capacities while ensuring the performance targets is a complex problem. This paper proposes a robust-optimization based approximation for the patient waiting times in an A&E.We also develop a simulation optimization heuristic to solve this capacity planning problem. The performance of the approximation approach is then compared with that of the simulation optimization heuristic. Finally, the impact of model parameters on the performances of two approaches is investigated. The experiments show that the proposed approximation results in good enough solutions.

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“…Jabatan kecemasan di sesebuah hospital merupakan jabatan yang paling sibuk dalam industri perkhidmatan kesihatan bukan sahaja di Malaysia malahan di seluruh dunia (Al-Refaie et al 2014;Aminuddin et al 2016;Ibrahim et al 2018a;McHugh et al 2011). Jabatan ini beroperasi 24 jam sehari sepanjang tahun tanpa cuti.…”

Section: Pendahuluanunclassified

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

Yusoff

Liong²,

Noh

et al. 2019

JSM

Self Cite

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(JKHUSM) telah menunjukkan perubahan yang pesat dan menghadapi transformasi drastik berhubung dengan kepentingan dalam sistem penjagaan kesihatan. Peramalan dan perancangan sumber yang munasabah perlu dilakukan bagi memenuhi permintaan pesakit yang kian bertambah. Justeru, kajian ini memfokuskan kepada Zon Kuning di JKHUSM yang memerlukan perancangan sewajarnya atas keperluan sumber yang sepatutnya disediakan pada masa kini dan akan datang untuk membantu pihak pengurusan dalam perancangan strategik jabatan serta menambah baik aliran pesakit dan perkhidmatan di zon tersebut. Pemodelan Sistem Dinamik telah dibangunkan untuk meramalkan bilangan pesakit yang akan berkunjung serta jumlah sumber yang diperlukan untuk memenuhi permintaan perkhidmatan di Zon Kuning JKHUSM pada masa sekarang (2014) dan masa hadapan bagi tempoh lima (2019) dan sepuluh tahun akan datang (2024). Hasil kajian meramalkan sumber yang diperlukan bagi memenuhi permintaan pesakit yang berkunjung di Zon Kuning pada masa sekarang adalah seramai 11 orang doktor, 12 orang jururawat dan 18 buah katil berbanding dengan sembilan orang doktor, sembilan orang jururawat dan 16 buah katil sedia ada. Seterusnya penambahan dua buah katil diramalkan untuk memenuhi keperluan pesakit bagi tempoh lima dan sepuluh tahun akan datang. Manakala tiada penambahan doktor dan jururawat diperlukan bagi memenuhi permintaan pesakit bagi tempoh lima tahun akan datang. Namun begitu dijangkakan penambahan seorang doktor dan seorang jururawat diperlukan bagi memenuhi permintaan 10 tahun akan datang. Oleh itu, peramalan penambahan sumber ini adalah sangat penting untuk menambah baik aliran pesakit di Zon Kuning JKHUSM serta membantu dalam mencapai Penunjuk Prestasi Utama jabatan ini. Hasil kajian yang diperoleh akan membantu pihak pengurusan membuat keputusan yang wajar dengan belanjawan yang telah ditetapkan demi meningkatkan kualiti perkhidmatan yang ditawarkan di samping meningkatkan tahap prestasi Zon Kuning JKHUSM.

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Estimating optimal resource capacities in emergency department

Cited by 5 publications

References 0 publications

An integrated approach for designing in-time and economically sustainable emergency care networks: A case study in the public sector

An integrated approach for designing in-time and economically sustainable emergency care networks: A case study in the public sector

Robust capacity planning for accident and emergency services

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

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