Independent Researcher, Gothenburg, Sweden.
Department of Business Administration, University of Gothenburg, Gothenburg, Sweden.
J Infect Public Health. 2020 May;13(5):746-752. doi: 10.1016/j.jiph.2020.01.002. Epub 2020 Jan 27.
Nosocomial infection (NI) increased the rate of mortality, morbidity and financial load for patients and Healthcare Facilities (HFs). Regarding to many advances in controlling NIs, it is still a worldwide problem. Layout of HF (department configuration) has a vital role in controlling NIs, because the pathogen microorganisms can transmit among departments. Some departments can transmit microorganisms much more than the other departments, called cause, and some of them received the microorganisms more than the others, called effect. Both are risky.
This study attempts to propose a comprehensive algorithm for selecting low risky department(s) for upgrading of HFs by use of Multiple Criteria Decision-Making (MCDM) methods.
Among MCDM methods, this study has hybrid WSM and Expanded DEMATEL, beside modified Nominal Group Technique to minimize NIs risk in upgrading of HFs. The resulted decision-making algorithm is validated by implementing in a HF as a case study.
The final proposed algorithm and the resulted low risky departments are approved by head and manager of the HF. Therefore, the algorithm is valid, and the feasibility of algorithm is approved by achieving the result from implementing of algorithm in the case study.
To conclude, the proposed algorithm can be a solution to minimize the risks of NIs, while upgrading, in each HFs and make the decision of HF's managers easier and logic.
医院感染（NI）增加了患者和医疗机构（HFs）的死亡率、发病率和经济负担。尽管在控制 NIs 方面已经取得了许多进展，但这仍然是一个全球性的问题。HF 的布局（部门配置）在控制 NIs 方面起着至关重要的作用，因为病原体微生物可以在部门之间传播。有些部门比其他部门更容易传播微生物，称为原因，而有些部门比其他部门更容易接收微生物，称为效果。两者都有风险。
本研究试图通过使用多准则决策方法（MCDM）提出一种综合算法，用于选择风险较低的部门进行 HFs 的升级。
在 MCDM 方法中，本研究结合了 WSM 和扩展的 DEMATEL，以及改进的名义群体技术，以最小化 HFs 升级过程中的 NIs 风险。所得到的决策算法通过在一个 HF 中实施作为案例研究进行验证。
最终提出的算法和得到的低风险部门得到了 HF 的负责人和经理的认可。因此，该算法是有效的，并且通过在案例研究中实施算法来实现结果，算法的可行性得到了验证。
总之，所提出的算法可以为每个 HFs 在升级时最小化 NIs 风险提供解决方案，并使 HF 经理的决策更容易和更合乎逻辑。
