A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks

Abstract

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.

Evaluation of criteria and COVID-19 patients for intensive care unit admission in the era of pandemic: A multi-criteria decision making approach

“…While the criteria are weighted using AHP, the hospitals are ranked using technique for order preference by similarity to ideal solution (TOPSIS) approach regarding to the weighted criteria. Another hybrid approach is conducted by Parsia and Sorooshian [44] . In their study, the criteria related with the minimization of nosocomial infections risks are weighted using decision-making trial and evaluation laboratory (DEMATEL) and WSM.…”

“… Fei et al [26] BWM Assessment of hospital service quality. Parsia and Sorooshian [44] DEMATEL and WSM Minimization of nosocomial infections risks. De Nardo et al [15] PAPRIKA Weighting the criteria for COVID-19 non-critical patients for admission to hospital under scarce resources.…”

Emergency architecture. Modular construction of healthcare facilities as a response to pandemic outbreak

“…The development of modular prefabricated systems plays a vital role in global preparedness to catastrophic events and occurrence of novel diseases where emergency response is needed, and therefore reflects on a number of lives that can be saved [23,24].…”

Hospital reconversion in response to the COVID-19 pandemic using simulation and multi-objective genetic algorithms

“…The authors argue that there is a lack of rigorous evidence linking hospital facility layouts with the prevention of nosocomial infections and that it is mainly due to the multifactorial nature of those infections; however, certain improvements could be seen if basic conditions, such as the sufficient availability of space and the insulation capacity, were improved. Parsia & Sorooshian (2020) argue that health care facility design plays a significant role in controlling nosocomial infections. They propose a mathematical algorithm seeking to minimize the nosocomial infection rate by restructuring hospital facilities.…”