Evidence map›Paper›PMID 36944917›Full record

ArticleBMC infectious diseases2023

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

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

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Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Antimicrobial approach of abdominal post-surgical infections.World journal of gastrointestinal surgery · 2023
    Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Naser NasiriDepartment of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
Ali SharifiDepartment of Ophthalmology, Shafa Hospital, Afzalipour School of Medicine, Kerman University of Medical Sciences, Kerman, Iran. a_sharifi@kmu.ac.ir.
Iman GhasemzadehHIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Malahat KhaliliHIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Ali KaramoozianModeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Islamic Republic of Iran.
Ali KhalooeiSocial Determinants of Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Amin BeigzadehSirjan School of Medical Sciences, Sirjan, Iran.
AliAkbar HaghdoostDepartment of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
Hamid SharifiDepartment of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran. sharifihami@gmail.com.

Funding

Kerman University of Medical Sciences 400000394
6 · The paper itself

Abstract

backgroundHealthcare-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.

methodsIn 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.

resultsAmong 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.

conclusionsThe 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.

Indexed as

Cross InfectionUrinary Tract InfectionsDelivery of Health CareHumansIncidenceIranLongitudinal StudiesAccuracyHealthcare-associated infectionsIncidence rateSurveillance system

Identifiers

PMID36944917
PMCPMC10031858

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.