Independent Researcher, Gothenburg, Sweden.
Department of Business Administration, University of Gothenburg, Gothenburg, Sweden.
Int J Environ Res Public Health. 2020 Jan 30;17(3):855. doi: 10.3390/ijerph17030855.
Most of the healthcare facilities (HFs) have to face the nosocomial infections (NIs), which increase the rates of morbidity, mortality, and financial burden on the HFs and the patients. The control of the NIs is a global issue and requires additional effort. Because the pathogenic microbes can be transmitted among all the HF departments, the layout and design of the HFs (or the department configuration) is considered to play a significant role in control of the NIs. A few of the departments transmit the microbes more than other departments, called 'cause', while some other departments are more infected than others, called 'effect'. Here, the researchers have stated that both the cause and effect departments are risky. This research tried to propose a comprehensive mathematical algorithm for choosing the high-risk department(s) by applying the NI and the managerial criteria to minimize NIs through rearchitecting of the HFs. To develop the algorithm, the researchers applied the multiple criteria decision-making (MCDM) methods. They used Decision-Making Trial and Evaluation Laboratory (DEMATEL) and modified weighted sum method (WSM) methods, and their hybrid, along with a modified nominal group technique (NGT) for data collection. The proposed algorithm was later validated by implementation in a HF as a case study. Based on all results of the algorithm, the high-risk departments in the HF were identified and proposed to be eliminated from the HF in such a way that the facility would retain its functionality. The algorithm was seen to be valid, and the feasibility of the algorithm was approved by the top managers of the HF after the algorithm was implemented in the case study. In conclusion, the proposed algorithm was seen to be an effective solution for minimizing the NIs risk in every HF by eliminating the high-risk departments, which could simplify the HF manager's decisions.
大多数医疗机构（HFs）都必须应对医院获得性感染（NIs），这会增加发病率、死亡率以及医疗机构和患者的经济负担。控制 NIs 是一个全球性问题，需要额外的努力。由于病原体可以在所有 HF 科室之间传播，因此 HFs 的布局和设计（或科室配置）被认为在控制 NIs 方面发挥着重要作用。一些科室比其他科室更容易传播微生物，称为“原因”，而其他一些科室比其他科室更容易感染，称为“效果”。在这里，研究人员指出，原因和效果科室都是有风险的。本研究试图通过应用 NI 和管理标准，通过重新构建 HFs 来最小化 NIs，提出一种选择高风险科室的综合数学算法。为了开发该算法，研究人员应用了多准则决策（MCDM）方法。他们使用决策试验和评估实验室（DEMATEL）和改进的加权和方法（WSM）及其混合方法，以及改进的名义群体技术（NGT）进行数据收集。然后，将所提出的算法在医疗机构中实施作为案例研究进行验证。根据算法的所有结果，确定了 HFs 中的高风险科室，并提出将其从 HFs 中消除，以使该设施保持其功能。算法被证明是有效的，并且在案例研究中实施该算法后，HF 的高层管理人员批准了该算法的可行性。总之，该算法被视为通过消除高风险科室来降低每个 HFs 中 NIs 风险的有效解决方案，这可以简化 HF 经理的决策。
