Optimizing human resource cost of an emergency hospital using multi-objective Bat algorithm

Apornak, Arash; Raissi, Sadigh; Keramati, Abbas; Khalili‐Damghani, Kaveh

doi:10.1080/20479700.2019.1707415

Cited by 22 publications

(12 citation statements)

References 19 publications

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“…This not only supports previous similar findings in other settings [5] but also highlights new information on potential long-term effects of regularly putting the spotlight on frequent and relatively complicated pathologies encountered by medical professionals. As a management strategy, holding educational workshops at the beginning of shifts has implications on the organization of the work: this strategy could be sustainable if workshops have long-lasting effects [11] on the improvement professional practices and therefore, they take place in a limited time.…”

Section: Discussionmentioning

confidence: 99%

Adoption of new guidelines for the management of acute heart failure in the emergency department: An assessment on the quality of practice

Zula

Briganti

2020

International Journal of Healthcare Management

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Background: Acute heart failure (AHF) is a disease with high incidence and mortality. Since 2016, new definitions were adopted for AHF requiring early management to improve prognosis. The aim of this study is to assess practices regarding management of AHF before and after a standardized educational workshop, which was delivered to emergency physicians and nurses during work shifts. Methods: 146 patients presenting AHF were selected in this prospective study. Patients were divided in three groups for three different periods, namely a first phase without educational workshops offered to emergency physicians and nurses, a second phase with educational workshops, and a third phase with assessment of practices after a six-month interval. Results: Systematic measurement of respiratory rare improved from 17% to 67% of cases. The acquirement of an echocardiography before the 24-hour delay improved from 21% to 100% of cases. The administration of diuretics also improved from 79% to 84% of cases. Conclusions: An improvement of diagnostic and therapeutic management was found. Educational workshops to emergency physicians and nurses improve the clinical recognition of AHF, reduces the delay of the acquirement of echocardiography, and treatment administration.

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Section: Discussionmentioning

confidence: 99%

Adoption of new guidelines for the management of acute heart failure in the emergency department: An assessment on the quality of practice

Zula

Briganti

2020

International Journal of Healthcare Management

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“…PO is a common method that has been widely used to solve MOPs [6,8,12,23]. It tries to satisfy the whole objectives simultaneously.…”

Section: Pareto Optimizationmentioning

confidence: 99%

“…It generates a nondominated set of solutions for MOPs, which cannot be further optimized. PO has been applied to solve MOPs in different fields, such as clustering [7][8][9] and hospital resource optimization [10][11][12] PO can be employed to solve the admission problem considering the different objectives of the problem as it has been used before in [13].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

et al. 2021

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The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

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“…Moreover, multi-objective bat algorithm has been used to solve many real-life applications. Arash et al [30] proposed a multi-objective Bat algorithm for optimizing the cost for allocating human resources to an emergency hospital. Anindita et al [31] proposed a bio-inspired algorithm for solving different aspects of wireless sensor network (WSN) like optimal routing, clustering, dynamic allocation of motes, lifetime optimization and the energy problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Many-objective BAT algorithm

2020

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In many objective optimization problems (MaOPs), more than three distinct objectives are optimized. The challenging part in MaOPs is to get the Pareto approximation (PA) with high diversity and good convergence. In Literature, in order to solve the issue of diversity and convergence in MaOPs, many approaches are proposed using different multi objective evolutionary algorithms (MOEAs). Moreover, to get better results, the researchers use the sets of reference points to differentiate the solutions and to model the search process, it further evaluates and selects the non-dominating solutions by using the reference set of solutions. Furthermore, this technique is used in some of the swarm-based evolutionary algorithms. In this paper, we have used some effective adaptations of bat algorithm with the previous mentioned approach to effectively handle the many objective problems. Moreover, we have called this algorithm as many objective bat algorithm (MaOBAT). This algorithm is a biologically inspired algorithm, which uses echolocation power of micro bats. Each bat represents a complete solution, which can be evaluated based on the problem specific fitness function and then based on the dominance relationship, non-dominated solutions are selected. In proposed MaOBAT, dominance rank is used as dominance relationship (dominance rank of a solution means by how many other solutions a solution dominated). In our proposed strategy, dynamically allocated set of reference points are used, allowing the algorithm to have good convergence and high diversity pareto fronts (PF). The experimental results show that the proposed algorithm has significant advantages over several state-of-the-art algorithms in terms of the quality of the solution.

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Optimizing human resource cost of an emergency hospital using multi-objective Bat algorithm

Cited by 22 publications

References 19 publications

Adoption of new guidelines for the management of acute heart failure in the emergency department: An assessment on the quality of practice

Adoption of new guidelines for the management of acute heart failure in the emergency department: An assessment on the quality of practice

A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Many-objective BAT algorithm

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