Construction of equipment alarm fatigue risk prediction model for pediatric ICU nurses
10.3760/cma.j.cn115682-20211006-04507
- VernacularTitle:儿科ICU护士仪器设备报警疲劳风险预测模型的构建
- Author:
Qiaohong LIU
1
;
Jie WANG
;
Yongke DUAN
;
Huiyue ZHOU
;
Ruihua QI
Author Information
1. 郑州大学附属儿童医院 河南省儿童医院 郑州儿童医院外科监护室，郑州 450000
- Keywords:
Pediatrics;
Nurses;
Intensive Care Unit;
Equipment alarm fatigue;
Risk;
Prediction model
- From:
Chinese Journal of Modern Nursing
2022;28(22):3016-3021
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the influencing factors of instrument and equipment alarm fatigue risk of nurses in pediatric intensive care unit (ICU) , establish a prediction model and verify its prediction efficiency.Methods:A multi-stage sampling method was used to select 300 pediatric ICU nurses from 2 tertiary children's specialized hospitals in Henan Province from October 2020 to March 2021 as the research objects for model construction. A total of 300 questionnaires were distributed and 225 valid questionnaires were recovered. From April to May 2021, 110 pediatric ICU nurses in Henan Children's Hospital were selected for model validation, 110 questionnaires were distributed and 100 valid questionnaires were recovered. A self-made baseline rating scale was used to collect relevant baseline information. The medical equipment alarm management questionnaire and the equipment alarm fatigue related scale were used for investigation. The Logistic regression model was used to establish the prediction model, Hosmer-Lemeshow test was used to test the fitting effect of the model and the receiver operating characteristic curve was used to evaluate the prediction value.Results:The 225 pediatric ICU nurses scored (48.67±4.35) for medical equipment alarm management factors, (39.67±3.67) for obstacles to medical equipment alarm management and (22.32±2.83) for clinical alarm fatigue. The results of multivariate analysis showed that the factors of age less than 30 years old, working years less than 5 years, working with illness, nurses with professional titles below, shift work, no habit of setting medical equipment alarms, and medical equipment management factors were all pediatric ICU nurses' equipment alarm fatigue. The independent risk factor of ICU ( P<0.05) . In this study, a prediction model was finally constructed. The area under the receiver operating characteristic curve (AUC) of the model was 0.887, the sensitivity was 0.891 and the specificity was 0.843. The validation data results showed that AUC value of the model was 0.901, the sensitivity was 0.912 and the specificity was 0.857. Conclusions:Pediatric ICU nurses have different degrees of equipment alarm fatigue. This research model can reliably predict the alarm fatigue risk of their equipment and equipment, suggesting that high-risk factors should be paid attention to and timely intervention measures should be carried out to reduce the risk of related adverse events.
