Should International Classification of Diseases codes be used to survey hospital-acquired pneumonia?

Wolfensberger, Aline; Meier, Angela; Kuster, Stefan P.; Mehra, Tarun; Meier, Marie-Theres; Sax, Hugo

doi:10.1016/j.jhin.2018.01.017

Cited by 20 publications

(36 citation statements)

References 7 publications

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“…By challenging our algorithm by full manual evaluation of the patient population diagnosed and coded to have HAP, we identified four additional patients with nvHAP. Knowing that the sensitivity of ICD-10 coded HAP for HAP according to ECDC definition in our hospital is around 60% [11], we anticipate having potentially missed another three patients maximumda small number compared to the 251 patients identified by our semi-automated surveillance system. By closely mirroring the ECDC surveillance criteria in our classification algorithm, the sensitivity of our semi-automated surveillance system is close to 100%, higher than the sensitivity of (semi-)automated surveillance systems for various HAIs summarized in the 2013 review by Van Mourik et al [5].…”

Section: Discussionmentioning

confidence: 95%

“…For nvHAP, we were not able to identify a study validating a (semi-)automated surveillance system. Instead, two investigations assessed discharge diagnostic codes to substitute conventional nvHAP surveillance with an overall poor sensitivity of 42% and 59% [11,20], which declassifies this approach for epidemiological surveillance purposes.…”

Section: Discussionmentioning

confidence: 99%

“…Three authors reported nvHAP incidence rates between 0.12 and 2.28 per 1000 patient days by applying the 2013 CDC surveillance definition to patients with International Classification of Diseases (ICD-9-CM) codes for pneumonia not present on admission [8e10]. These studies may reflect incidence of nvHAP only very roughly, as positive predictive value and sensitivity of discharge diagnostic codes for identifying patients with nvHAP were shown to be as low as 35% and 59%, respectively [11].…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of a semi-automated surveillance system—lowering the fruit for non-ventilator-associated hospital-acquired pneumonia (nvHAP) prevention

Wolfensberger

Jakob²,

Hesse

et al. 2019

Clinical Microbiology and Infection

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a b s t r a c tObjectives: Conducting manual surveillance of non-ventilator-associated hospital-acquired pneumonia (nvHAP) using ECDC (European Centre for Disease Prevention and Control) surveillance criteria is very resource intensive. We developed and validated a semi-automated surveillance system for nvHAP, and describe nvHAP incidence and aetiology at our hospital. Methods: We applied an automated classification algorithm mirroring ECDC definition criteria to distinguish patients 'not at risk' from patients 'at risk' for suffering from nvHAP. 'At risk'-patients were manually screened for nvHAP. For validation, we applied the reference standard of full manual evaluation to three validation samples comprising 2091 patients. Results: Among the 39 519 University Hospital Zurich inpatient discharges in 2017, the algorithm identified 2454 'at-risk' patients, reducing the number of medical records to be manually screened by 93.8%. From this subset, nvHAP was identified in 251 patients (0.64%, 95%CI: 0.57e0.73). Sensitivity, negative predictive value, and accuracy of semi-automated surveillance versus full manual surveillance were lowest in the validation sample consisting of patients with HAP according to the International Classification of Diseases (ICD-10) discharge diagnostic codes, with 97.5% (CI: 93.7e99.3%), 99.2% (CI: 97.9 e99.8%), and 99.4% (CI: 98.4e99.8%), respectively. The overall incidence rate of nvHAP was 0.83/1000 patient days (95%CI: 0.73e0.94), with highest rates in haematology/oncology, cardiac and thoracic surgery, and internal medicine including subspecialties. Conclusions: The semi-automated surveillance demonstrated a very high sensitivity, negative predictive value, and accuracy. This approach significantly reduces manual surveillance workload, thus making continuous nvHAP surveillance feasible as a pivotal element for successful prevention efforts.

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Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development and validation of a semi-automated surveillance system—lowering the fruit for non-ventilator-associated hospital-acquired pneumonia (nvHAP) prevention

Wolfensberger

Jakob²,

Hesse

et al. 2019

Clinical Microbiology and Infection

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“…Additionally, VAP identi cation via diagnostic scoring tools may underperform in select patient sub-populations (eg. Burns [33], surgical [34]) and has been shown to correlate poorly with International Classi cation of Diseases coding data, thereby limiting large-scale epidemiologic study [35,36]. a Agreement based on score: ≤ 0 (no agreement); 0.01-0.20 (slight); 0.21-0.40 (fair); 0.41-0.60 (moderate); 0.61-0.80 (substantial); and 0.81-1.00 (almost perfect agreement).…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Diagnostic Algorithms and Clinical Parameters to Diagnose Ventilator-Associated Pneumonia: A Prospective Observational Study

Rahimi–Bashar

Miller²,

Yaghoobi

et al. 2020

Preprint

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BACKGROUND: Suspicion and clinical criteria continue to serve as the foundation for ventilator-associated pneumonia (VAP) diagnosis, however the criteria used to diagnose VAP vary widely. Data from head-to-head comparisons of clinical diagnostic algorithms is lacking, thus a prospective observational study was performed to determine the performance characteristics of the Johanson criteria, Clinical Pulmonary Infection Score (CPIS), and Centers for Disease Control and Prevention’s National Healthcare Safety Network (CDC/NHSN) criteria as compared to Hospital in Europe Link for Infection Control through Surveillance (HELICS) reference standard. METHODS: A prospective observational cohort study was performed in three mixed medical-surgical ICUs from one academic medical center from 1 October 2016 to 30 April 2018. VAP diagnostic criteria were applied to each patient including CDC/NHSN, CPIS, HELICS and Johanson criteria. Tracheal cultures and serum procalcitonin values were obtained for each patient. RESULTS: Eighty-five patients were enrolled (VAP 45, controls 41), mean age 46.94±18.9 years with a male predominance (72.94%). Using HELICS as the reference standard, the true positive (TP; sensitivity) and false negative (FN; miss rate) rates were CDC/NHSN (TP 44%; FN 0%), CPIS (TP 43%; FN 1%), Johnson (TP 43%; FN 1%). The highest true negative rate was seen with CPIS. CPIS had the highest Youden index; CDC/NHSN had the lowest. The positive tracheal culture rate was 81.2%. The sensitivity for positive tracheal culture with the serum procalcitonin level >0.5 ng/ml was 51.8%. CDC/NHSN had the highest false positive correlation with tracheal aspirate cultures. CONCLUSION: VAP remains a considerable source of morbidity and mortality in modern ICUs. The optimal diagnostic method remains unclear. Using HELICS criteria as the reference standard, CPIS displayed greater diagnostic accuracy compared to CDC/NHSN and Johanson criteria. Accuracy was improved with the addition of serum procalcitonin >0.5 ng/ml, but not positive quantitative endotracheal aspirate culture.TRIAL REGISTRATION: Not indicated for this study type.

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“…. pneumoniae is an important nosocomial pathogen that can cause pneumonia, urinary tract infection, digestive tract infection, bloodstream infection, liver abscess and meningitis(12)(13)(14)(15)(16)(17). Infection outbreaks have been frequently reported in neonatal intensive care units.…”

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confidence: 99%

Co-outbreak of ST37 and a novel ST3006 Klebsiella pneumoniae from multi-site infection in a neonatal intensive care unit: a retrospective study

Chen

et al. 2018

Preprint

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21 sequencing; Neonatal intensive care unit 22 23 2 Summary 24 Background: The spread of carbapenem resistance among Klebsiella pneumoniae (K. 25 pneumoniae) is a major public health problem, particularly in neonatal intensive care 26 units (NICUs).27Aim: To describe the nosocomial co-outbreak of ST37 and a new sequence type 28 ST3006 K. pneumoniae, causing catheter-related bloodstream infections in NICU. 29Methods: Fifteen strains of K. pneumoniae were isolated from seven neonates during 30 June 3-28, 2013, in a tertiary hospital neonatal intensive care unit in Fujian, China. 31Antimicrobial susceptibility was determined by the Vitek 2 system and micro-broth 32 dilution method. Multi-locus sequence typing (MLST) and pulsed-field gel 33 electrophoresis (PFGE) were used to analyse the genetic relatedness of isolates. 34Genome sequencing and gene function analyses were performed for investigating 35 pathogenicity and drug resistance and screening genomic islands. 36Findings: Two K. pneumoniae clones were identified from seven neonates with 37 multi-site infection, one ST37 strain and one new sequence type ST3006. 38Antimicrobial susceptibility testing revealed that the ST37 strain exhibited multi-drug 39 resistance and carbapenem resistance. The ST3006 strain was only resistant to 40 ampicillin-sulbactam, cefazolin, ceftriaxone. MLST and PFGE showed that 15 strains 41 were divided into three groups, with a high level of homology. Gene sequencing and 42 analysis indicated that KPN1343 harboured 12 resistance genes, 15 genomic islands 43 and 205 reduced virulence genes. KPN1344 harboured four resistance genes, 19 44 genomic islands and 209 reduced virulence genes. 45 Conclusion: Co-outbreak of K. pneumoniae involved two clones, ST36 and ST3006, 46 causing multi-site infection. Genome sequencing and analysis is an effective method 47 for studying bacterial resistance genes and their functions.48 49 50 Introduction 51 Klebsiella pneumonia, particularly multidrug resistant K. pneumoniae, is a 52 common and important pathogen in hospitals, posing a serious and urgent threat to 53 public health (1, 2). Neonates in the neonatal intensive care units often have 54 underlying conditions, such as prematurity, or the presence of indwelling catheters, a 55 history of antibiotic treatment and parenteral nutrition, which are risk factors for 56 infection (3). In addition, relaxed vigilance by doctors and nurses regarding 57 nosocomial infection promotes nosocomial infection outbreaks, with considerable 58 impact on neonatal treatment and prognosis, prolonged hospital stays, increased 59 hospital costs and mortality. 60 Nosocomial outbreaks in the neonatal intensive care unit are frequently reported 61(4-7); however, it is rare to isolate the same clonal pathogen from different sites in the 62 same patient. This study identified 15 K. pneumoniae strains isolated from sputum 63 specimens, blood specimens and umbilical vein catheter tips in seven neonates that 64 belonged to the two cloned strains ST37 and ST3006, which produced carb...

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Should International Classification of Diseases codes be used to survey hospital-acquired pneumonia?

Cited by 20 publications

References 7 publications

Development and validation of a semi-automated surveillance system—lowering the fruit for non-ventilator-associated hospital-acquired pneumonia (nvHAP) prevention

Development and validation of a semi-automated surveillance system—lowering the fruit for non-ventilator-associated hospital-acquired pneumonia (nvHAP) prevention

A Comparison of Diagnostic Algorithms and Clinical Parameters to Diagnose Ventilator-Associated Pneumonia: A Prospective Observational Study

Co-outbreak of ST37 and a novel ST3006 Klebsiella pneumoniae from multi-site infection in a neonatal intensive care unit: a retrospective study

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