{"title":"A simulation-based approach for decision-support in healthcare processes","authors":"Mercedes Ruiz , Elena Orta , Juan Sánchez","doi":"10.1016/j.simpat.2024.102983","DOIUrl":null,"url":null,"abstract":"<div><p>This article explores the application of simulation-driven decision support systems in the context of healthcare processes. The findings obtained from the review of related research suggest that simulation models have been widely used in the healthcare sector as valuable tools to aid decision-making aimed at the improvement of healthcare process management. However, the analyzed works lack sufficient evidence regarding the utilization of systematic approaches in the development of their proposals. We have conducted a research effort in this field, resulting in the design of a conceptual framework that guides in the systematic development of decision support systems centered around simulation models. The framework includes a specific methodology for developing simulation models, with simulation modeling experimentation serving as a valuable technique for assessing the impact of potential changes on the performance of the process. To illustrate the applicability and practical value of the proposed framework, we have developed an application case within the context of the Urgent Healthcare for Women's (UHW) process in a public hospital in Andalusia, Spain.</p></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"136 ","pages":"Article 102983"},"PeriodicalIF":3.5000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1569190X24000972/pdfft?md5=c308a2d43bcfa682ce36d94a7d002368&pid=1-s2.0-S1569190X24000972-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Simulation Modelling Practice and Theory","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569190X24000972","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This article explores the application of simulation-driven decision support systems in the context of healthcare processes. The findings obtained from the review of related research suggest that simulation models have been widely used in the healthcare sector as valuable tools to aid decision-making aimed at the improvement of healthcare process management. However, the analyzed works lack sufficient evidence regarding the utilization of systematic approaches in the development of their proposals. We have conducted a research effort in this field, resulting in the design of a conceptual framework that guides in the systematic development of decision support systems centered around simulation models. The framework includes a specific methodology for developing simulation models, with simulation modeling experimentation serving as a valuable technique for assessing the impact of potential changes on the performance of the process. To illustrate the applicability and practical value of the proposed framework, we have developed an application case within the context of the Urgent Healthcare for Women's (UHW) process in a public hospital in Andalusia, Spain.
期刊介绍:
The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling.
The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas.
Paper submission is solicited on:
• theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.;
• methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.;
• simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.;
• distributed and real-time simulation, simulation interoperability;
• tools for high performance computing simulation, including dedicated architectures and parallel computing.