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用于优化 ICU 车辆布局的混合整数规划模型。

Mixed integer programming model for optimizing the layout of an ICU vehicle.

机构信息

Department of 'Ingeniería de Organización, Administración de Empresas y Estadística', Escuela Técnica Superior de Ingenieros Industriales, Universidad Politécnica de Madrid, Madrid, Spain.

出版信息

BMC Health Serv Res. 2009 Dec 8;9:224. doi: 10.1186/1472-6963-9-224.

DOI:10.1186/1472-6963-9-224
PMID:19995438
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2797005/
Abstract

BACKGROUND

This paper presents a Mixed Integer Programming (MIP) model for designing the layout of the Intensive Care Units' (ICUs) patient care space. In particular, this MIP model was developed for optimizing the layout for materials to be used in interventions. This work was developed within the framework of a joint project between the Madrid Technical Unverstity and the Medical Emergency Services of the Madrid Regional Government (SUMMA 112).

METHODS

The first task was to identify the relevant information to define the characteristics of the new vehicles and, in particular, to obtain a satisfactory interior layout to locate all the necessary materials. This information was gathered from health workers related to ICUs. With that information an optimization model was developed in order to obtain a solution. From the MIP model, a first solution was obtained, consisting of a grid to locate the different materials needed for the ICUs. The outcome from the MIP model was discussed with health workers to tune the solution, and after slightly altering that solution to meet some requirements that had not been included in the mathematical model, the eventual solution was approved by the persons responsible for specifying the characteristics of the new vehicles. According to the opinion stated by the SUMMA 112's medical group responsible for improving the ambulances (the so-called "coaching group"), the outcome was highly satisfactory. Indeed, the final design served as a basis to draw up the requirements of a public tender.

RESULTS

As a result from solving the Optimization model, a grid was obtained to locate the different necessary materials for the ICUs. This grid had to be slightly altered to meet some requirements that had not been included in the mathematical model. The results were discussed with the persons responsible for specifying the characteristics of the new vehicles.

CONCLUSION

The outcome was highly satisfactory. Indeed, the final design served as a basis to draw up the requirements of a public tender. The authors advocate this approach to address similar problems within the field of Health Services to improve the efficiency and the effectiveness of the processes involved. Problems such as those in operation rooms or emergency rooms, where the availability of a large amount of material is critical are eligible to be dealt with in a simmilar manner.

摘要

背景

本文提出了一种混合整数规划(MIP)模型,用于设计重症监护病房(ICU)患者护理空间的布局。特别是,这个 MIP 模型是为优化干预措施中使用的材料布局而开发的。这项工作是在马德里技术大学和马德里地区政府医疗急救服务(SUMMA 112)之间的联合项目框架内进行的。

方法

首先要确定相关信息,以定义新车辆的特点,特别是要获得一个满意的内部布局,以放置所有必要的材料。这些信息是从与 ICU 相关的卫生工作者那里收集的。有了这些信息,就可以开发一个优化模型来获得解决方案。从 MIP 模型中,我们得到了一个初步的解决方案,即一个用于定位 ICU 所需不同材料的网格。MIP 模型的结果与卫生工作者进行了讨论,以调整解决方案,并且在稍微改变解决方案以满足一些未包含在数学模型中的要求后,最终解决方案得到了负责指定新车辆特点的人员的批准。根据 SUMMA 112 的医疗小组(即所谓的“教练组”)提出的意见,结果非常令人满意。事实上,最终的设计为制定公开招标的要求提供了基础。

结果

通过解决优化模型,我们得到了一个用于定位 ICU 所需不同材料的网格。这个网格需要稍微改变,以满足一些未包含在数学模型中的要求。结果与负责指定新车辆特点的人员进行了讨论。

结论

结果非常令人满意。事实上,最终的设计为制定公开招标的要求提供了基础。作者提倡这种方法来解决卫生服务领域的类似问题,以提高所涉及过程的效率和效果。在手术室或急诊室等情况下,大量材料的可用性至关重要,这些问题可以以类似的方式处理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/d65e41ba538a/1472-6963-9-224-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/b090606bd135/1472-6963-9-224-1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/2720c0e637ff/1472-6963-9-224-3.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/d65e41ba538a/1472-6963-9-224-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/b090606bd135/1472-6963-9-224-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/5c9787adc08d/1472-6963-9-224-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/2720c0e637ff/1472-6963-9-224-3.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e65/2797005/d65e41ba538a/1472-6963-9-224-5.jpg

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