PMID- 32001195
OWN - NLM
STAT- MEDLINE
DCOM- 20201125
LR  - 20201125
IS  - 1876-035X (Electronic)
IS  - 1876-0341 (Linking)
VI  - 13
IP  - 5
DP  - 2020 May
TI  - Minimization of nosocomial infections risks by a decision algorithm for upgrading 
      of healthcare facilities.
PG  - 746-752
LID - S1876-0341(20)30002-2 [pii]
LID - 10.1016/j.jiph.2020.01.002 [doi]
AB  - 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.
CI  - Copyright (c) 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.
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. Electronic address: Sorooshian@gmail.com.
LA  - eng
PT  - Journal Article
DEP - 20200127
PL  - England
TA  - J Infect Public Health
JT  - Journal of infection and public health
JID - 101487384
SB  - IM
MH  - *Algorithms
MH  - Cross Infection/epidemiology/*prevention & control/transmission
MH  - *Decision Making
MH  - *Health Facilities
MH  - Humans
MH  - Infection Control/methods
MH  - Risk Management
OTO - NOTNLM
OT  - Decision making
OT  - Healthcare facility
OT  - Nosocomial infection
OT  - Risky department(s)
OT  - Upgrading
EDAT- 2020/02/01 06:00
MHDA- 2020/11/26 06:00
CRDT- 2020/02/01 06:00
PHST- 2019/10/26 00:00 [received]
PHST- 2020/01/15 00:00 [accepted]
PHST- 2020/02/01 06:00 [pubmed]
PHST- 2020/11/26 06:00 [medline]
PHST- 2020/02/01 06:00 [entrez]
AID - S1876-0341(20)30002-2 [pii]
AID - 10.1016/j.jiph.2020.01.002 [doi]
PST - ppublish
SO  - J Infect Public Health. 2020 May;13(5):746-752. doi: 10.1016/j.jiph.2020.01.002. 
      Epub 2020 Jan 27.