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

© 2023. The Author(s)..

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:23

Enthalten in:

BMC infectious diseases - 23(2023), 1 vom: 21. März, Seite 171

Sprache:

Englisch

Beteiligte Personen:

Nasiri, Naser [VerfasserIn]
Sharifi, Ali [VerfasserIn]
Ghasemzadeh, Iman [VerfasserIn]
Khalili, Malahat [VerfasserIn]
Karamoozian, Ali [VerfasserIn]
Khalooei, Ali [VerfasserIn]
Beigzadeh, Amin [VerfasserIn]
Haghdoost, AliAkbar [VerfasserIn]
Sharifi, Hamid [VerfasserIn]

Links:

Volltext

Themen:

Accuracy
Healthcare-associated infections
Incidence rate
Journal Article
Surveillance system

Anmerkungen:

Date Completed 23.03.2023

Date Revised 24.03.2023

published: Electronic

Citation Status MEDLINE

doi:

10.1186/s12879-023-08122-1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM354501704