PMID- 32019085
OWN - NLM
STAT- MEDLINE
DCOM- 20200911
LR  - 20200911
IS  - 1660-4601 (Electronic)
IS  - 1661-7827 (Print)
IS  - 1660-4601 (Linking)
VI  - 17
IP  - 3
DP  - 2020 Jan 30
TI  - A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to 
      Minimize Nosocomial Infections Risks.
LID - 10.3390/ijerph17030855 [doi]
LID - 855
AB  - 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.
FAU - Parsia, Yasaman
AU  - Parsia Y
AD  - Independent Researcher, Gothenburg, Sweden.
FAU - Sorooshian, Shahryar
AU  - Sorooshian S
AD  - Department of Business Administration, University of Gothenburg, Gothenburg, 
      Sweden.
LA  - eng
PT  - Journal Article
DEP - 20200130
PL  - Switzerland
TA  - Int J Environ Res Public Health
JT  - International journal of environmental research and public health
JID - 101238455
SB  - IM
MH  - *Algorithms
MH  - Architecture
MH  - Cross Infection/*etiology/*prevention & control
MH  - *Decision Making
MH  - *Health Facilities
MH  - Health Services
MH  - Humans
MH  - Research Design
MH  - *Risk Management
PMC - PMC7037869
OTO - NOTNLM
OT  - healthcare facility
OT  - multiple criteria decision making
OT  - nosocomial infection
OT  - rearchitecting
OT  - risky department(s)
COIS- No potential conflict of interest was reported by the authors.
EDAT- 2020/02/06 06:00
MHDA- 2020/09/12 06:00
PMCR- 2020/02/01
CRDT- 2020/02/06 06:00
PHST- 2019/11/26 00:00 [received]
PHST- 2020/01/23 00:00 [revised]
PHST- 2020/01/23 00:00 [accepted]
PHST- 2020/02/06 06:00 [entrez]
PHST- 2020/02/06 06:00 [pubmed]
PHST- 2020/09/12 06:00 [medline]
PHST- 2020/02/01 00:00 [pmc-release]
AID - ijerph17030855 [pii]
AID - ijerph-17-00855 [pii]
AID - 10.3390/ijerph17030855 [doi]
PST - epublish
SO  - Int J Environ Res Public Health. 2020 Jan 30;17(3):855. doi: 
      10.3390/ijerph17030855.