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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, A; Jakob, W; Faes Hesse, M; Kuster, S P; Meier, A H; Schreiber, P W; Clack, L; Sax, H (2019). Development and validation of a semi-automated surveillance system-lowering the fruit for non-ventilator-associated hospital-acquired pneumonia (nvHAP) prevention. Clinical Microbiology and Infection, 25(11):1428.e7-1428.e13.

Abstract

OBJECTIVES
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: 0.57-0.73). 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: 93.7-99.3%), 99.2% (CI: 97.9-99.8%), and 99.4% (CI: 98.4-99.8%), respectively. The overall incidence rate of nvHAP was 0.83/1000 patient days (95%CI: 0.73-0.94), 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.

Abstract

OBJECTIVES
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: 0.57-0.73). 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: 93.7-99.3%), 99.2% (CI: 97.9-99.8%), and 99.4% (CI: 98.4-99.8%), respectively. The overall incidence rate of nvHAP was 0.83/1000 patient days (95%CI: 0.73-0.94), 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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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Infectious Diseases
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:1 November 2019
Deposited On:09 Aug 2019 08:51
Last Modified:23 Oct 2019 01:03
Publisher:Elsevier
ISSN:1198-743X
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.cmi.2019.03.019
PubMed ID:30922931

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