Operations research as a decision-making tool in the health sector: A state of the art

Romero-Conrado, Alfonso R.; Bolaño, Lauren Julieth Castro; Montoya‐Torres, Jairo R.; Jimenez-Barros, Miguel A.

doi:10.15446/dyna.v84n201.57504

Cited by 9 publications

(5 citation statements)

References 71 publications

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“…Indeed, Silal and Modelling and Simulation Hub [29] pointed out that OR can help decision makers effectively manage infectious diseases while ensuring efficient resource allocation. Albeit often this discipline is widely applied in healthcare [110], its use has been limited in some way considering the difficulty to extract process data during the current outbreak. Unsurprisingly, the implementation of techniques from the QM area is scant which may be explained by the time that QM projects usually take for their development.…”

Section: Discussionmentioning

confidence: 99%

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

Ortíz‐Barrios

Coba-Blanco

Alfaro-Saiz

et al. 2021

IJERPH

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The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions.

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Section: Discussionmentioning

confidence: 99%

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

Ortíz‐Barrios

Coba-Blanco

Alfaro-Saiz

et al. 2021

IJERPH

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“…Given that trials and errors are non-viable, costly, and difficult to implement in the emergency care context, even in large-size ECNs; Discrete-event Simulation (DES) appears to be a suitable method for pretesting the performance of a recently designed ECN. In fact, the use of DES has become popular in the ED context [34]. For instance, Al-Assadi and Hasson utilized DES to maximize patients' throughput, minimize waiting times and optimize resources in Hilla ED [35].…”

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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“…Historical development, planning, optimization, and design making application of OR models in healthcare for public health are discussed in [5]. [6] Discusses the clinical problems, methods to optimize a system, and software facilitates the problem design.…”

Section: Introductionmentioning

confidence: 99%

A New Neuroinformatics Approach to Optimize Diagnosis Cost in Neurology: An Operational Research Tool

Hussain

Hussain²

2019

Int. J. Onl. Eng.

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<p>Cost optimization approach of operational research is a predictive power and economy of compactness that is applied to solve specific clinical needs relevant to healthcare cost reduction. Technology helps the healthcare management, decision making, and policy that we have implemented in the interest of improving quality of patient care and treatment outcomes, thereby reducing costs and improving efficiency. The treatment cost of brain tumor is high. Sometimes, cost becomes a problem for individuals to get their complete treatment, which makes their health at risk and may lead to higher cost in future. Here we address neuroinformatics approach to optimize diagnosis cost in neurology through an operational research tool (optimization) on how the diagnosis cost of neuro-patient can optimize. In this context, we introduce a new and unique optimization approach in healthcare, yet what we are clearly lacking for applying applications of operational tools to translate this understanding to the different level to apply the concept in healthcare. The costs of treatment achieved by three standard initial basic feasible solutions (IBFS) methods (North-west corner method, Minimum cost method, Vogel’s approximation method) are 763, 763, and 779. The optimal solution is 761, and three random tests (RT’s) are 826, 783, and 788. Optimal solution provided an overall difference in treatment cost with IBFS 2, 2, 18 and with RT’s 65, 22, and 27. These results establish the basis for a deliberate integration of operational research tools and neuroscience into diagnosis of cost optimization mechanisms for neuro- patient.</p>

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Operations research as a decision-making tool in the health sector: A state of the art

Cited by 9 publications

References 71 publications

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

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

A New Neuroinformatics Approach to Optimize Diagnosis Cost in Neurology: An Operational Research Tool

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