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Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran

BACKGROUND: Healthcare-associated infections (HAIs) are a threat to patients. Accurate surveillance is required to identify and prevent HAIs. To estimate the incidence rate, report the accuracy and identify the barriers of reporting HAIs using a mixed-method study. METHODS: In this quantitative stud...

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Autores principales: Nasiri, Naser, Sharifi, Ali, Ghasemzadeh, Iman, Khalili, Malahat, Karamoozian, Ali, Khalooei, Ali, Beigzadeh, Amin, Haghdoost, AliAkbar, Sharifi, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031858/
https://www.ncbi.nlm.nih.gov/pubmed/36944917
http://dx.doi.org/10.1186/s12879-023-08122-1
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author Nasiri, Naser
Sharifi, Ali
Ghasemzadeh, Iman
Khalili, Malahat
Karamoozian, Ali
Khalooei, Ali
Beigzadeh, Amin
Haghdoost, AliAkbar
Sharifi, Hamid
author_facet Nasiri, Naser
Sharifi, Ali
Ghasemzadeh, Iman
Khalili, Malahat
Karamoozian, Ali
Khalooei, Ali
Beigzadeh, Amin
Haghdoost, AliAkbar
Sharifi, Hamid
author_sort Nasiri, Naser
collection PubMed
description BACKGROUND: Healthcare-associated infections (HAIs) are a threat to patients. Accurate surveillance is required to identify and prevent HAIs. To estimate the incidence rate, report the accuracy and identify the barriers of reporting HAIs using a mixed-method study. METHODS: In this quantitative study, we externally evaluated the incidence rate and accuracy of the routine surveillance system in one of the main hospitals by an active follow-up of patients from September to December 2021. We used in-depth interviews with 18 experts to identify the barriers of the routine surveillance system. RESULTS: Among 404 hospitalized patients, 88 HAIs were detected. The estimated rate of HAIs was 17.1 (95% Confidence Intervals 95: 14.1, 21.1) per 1000 patient-days follow-up. However, in the same period, 116 HAIs were reported by the routine surveillance system, but the agreement between the two approaches was low (sensitivity = 61.4%, specificity = 82.6%, negative predictive value = 89.7%, and positive predictive validity = 46.5%). The minimum and maximum positive predictive values were observed in urinary tract infection (32.3%) and surgical site infection (60.9%). The main barrier of reporting HAIs was lack of cooperation in reporting HAIs by infection control link nurses and laboratory supervisors. CONCLUSIONS: The discrepancy between the longitudinal study findings and the routine surveillance might be related to the inaccessibility of the surveillance system to clinical information of patients. In this regard, decreasing the barriers, increasing the knowledge of infection control nurses and other nurses, as well as the development of hospital information systems are necessary.
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spelling pubmed-100318582023-03-23 Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran Nasiri, Naser Sharifi, Ali Ghasemzadeh, Iman Khalili, Malahat Karamoozian, Ali Khalooei, Ali Beigzadeh, Amin Haghdoost, AliAkbar Sharifi, Hamid BMC Infect Dis Research BACKGROUND: Healthcare-associated infections (HAIs) are a threat to patients. Accurate surveillance is required to identify and prevent HAIs. To estimate the incidence rate, report the accuracy and identify the barriers of reporting HAIs using a mixed-method study. METHODS: In this quantitative study, we externally evaluated the incidence rate and accuracy of the routine surveillance system in one of the main hospitals by an active follow-up of patients from September to December 2021. We used in-depth interviews with 18 experts to identify the barriers of the routine surveillance system. RESULTS: Among 404 hospitalized patients, 88 HAIs were detected. The estimated rate of HAIs was 17.1 (95% Confidence Intervals 95: 14.1, 21.1) per 1000 patient-days follow-up. However, in the same period, 116 HAIs were reported by the routine surveillance system, but the agreement between the two approaches was low (sensitivity = 61.4%, specificity = 82.6%, negative predictive value = 89.7%, and positive predictive validity = 46.5%). The minimum and maximum positive predictive values were observed in urinary tract infection (32.3%) and surgical site infection (60.9%). The main barrier of reporting HAIs was lack of cooperation in reporting HAIs by infection control link nurses and laboratory supervisors. CONCLUSIONS: The discrepancy between the longitudinal study findings and the routine surveillance might be related to the inaccessibility of the surveillance system to clinical information of patients. In this regard, decreasing the barriers, increasing the knowledge of infection control nurses and other nurses, as well as the development of hospital information systems are necessary. BioMed Central 2023-03-21 /pmc/articles/PMC10031858/ /pubmed/36944917 http://dx.doi.org/10.1186/s12879-023-08122-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Nasiri, Naser
Sharifi, Ali
Ghasemzadeh, Iman
Khalili, Malahat
Karamoozian, Ali
Khalooei, Ali
Beigzadeh, Amin
Haghdoost, AliAkbar
Sharifi, Hamid
Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran
title Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran
title_full Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran
title_fullStr Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran
title_full_unstemmed Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran
title_short Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran
title_sort incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast iran
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031858/
https://www.ncbi.nlm.nih.gov/pubmed/36944917
http://dx.doi.org/10.1186/s12879-023-08122-1
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