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

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.

Keywords: Automated surveillance; Electronic medical records; Hospital-acquired infections; Hospital-acquired pneumonia; Infection prevention.