Development and Validation of Selection Algorithms for a Non-Ventilator Hospital-Acquired Pneumonia (nvhap) Semi-Automated Surveillance System

Anna Mueller, Marc Pfister,Mirjam Faes Hesse,Walter Zingg,Aline Wolfensberger

Clinical Microbiology and Infection（2024）

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Abstract

Objectives Semi-automated surveillance systems save time compared to traditional manual methods, particularly for non-ventilator hospital-acquired pneumonia (nvHAP), a nosocomial infection which can affect all non-intubated patients. In semi-automated surveillance, a computerized algorithm selects patients with high probability (i.e. ‘at risk’) for subsequent manual confirmation. This study aimed to evaluate the performance of several single indicators and algorithms to preselect patients at risk for nvHAP. Methods Single nvHAP indicators, identified based on literature, expert opinion and data availability, were combined to simple and complex algorithms. Both single indicators and algorithms were applied on a patient cohort of 157’902 patients, including 947 patients with nvHAP according to our reference standard, i.e. validated semi-automated nvHAP surveillance system plus the manual surveillance of patients with ICD-10 discharge diagnostic codes. Performance characteristics like sensitivity, workload reduction, and number of patients needed to be screened to detect one case of nvHAP were assessed. Results Compared to the reference standard, single indicators had a sensitivity ranging from 35.1% (332/947) (oxygen desaturation) to 99.7% (944/947) (radiologic procedure). The workload reduction varied from 57.3% (90’505/157’902) (length of hospital stay >5d) to 98.4% (155’453/157’902) (ICD-10 discharge diagnostic code). The highest workload reduction was found in complex algorithms, e.g., the combination "radiologic procedure including full text AND temporally related abnormal white blood count or fever AND antimicrobials AND C-reactive protein AND decreased oxygenation AND hospital stay ≥5 days AND no intubation" which reduced the number of patients who have to undergo manual review by 96.2% (151’867/157’902), while maintaining a sensitivity of 92% (871/947). The number needed to screen applying this algorithm was 6.4 patients. Conclusions Several single indicators and algorithms showed a high workload reduction and a sensitivity above the defined threshold of 90%. Our results could assist hospitals or stakeholders of surveillance-initiatives in developing algorithms customized to their local conditions.

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Key words

Electronically assisted surveillance,Non-ventilator hospital-acquired pneumonia,Semi-automated surveillance,Surveillance

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【要点】：本研究评估了多种单一指标和算法在半自动化监测系统中预选非机械通气医院获得性肺炎（nvHAP）高危患者的性能，发现复杂算法能有效降低工作负担并保持高敏感性。

【方法】：通过文献研究、专家意见和数据可用性确定单一nvHAP指标，并组合成简单和复杂算法，应用于157,902名患者队列，其中包括947名nvHAP患者。

【实验】：实验使用了包含947名nvHAP患者的157,902名患者队列数据，通过比较单一指标和算法的性能，如敏感性、工作负担减少比例和每检测一例nvHAP所需筛查的患者数量，发现复杂算法能有效减少需手动审查的患者数量，同时维持92%的敏感性。