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

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.

Minimization of nosocomial infections risks by a decision algorithm for upgrading of healthcare facilities.

BACKGROUND: 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. OBJECTIVE: 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. METHODOLOGY: 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. RESULTS: 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. CONCLUSION: 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.

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