Implementing a screening algorithm for early recognition of sepsis in hospitalized children: a quality improvement project.

Sepsis is a leading cause of mortality in children. Utilizing a screening tool for early recognition of sepsis is recommended. Our centre had no screening tool for sepsis nor a standardized protocol for sepsis management. In December 2020, a screening algorithm for sepsis was implemented. The algorithm consisted of vital signs measurements in children with an abnormal body temperature, a pop-up alert, nurse's and physician's evaluation, and activation of a workup protocol. The project's primary aim was to increase vital signs measurement rates in hospitalized children with abnormal body temperature from 40% to >90% within 6 months, by 1 June 2021, and sustain until 31 December 2021. Adherence to the algorithm and performance were monitored during 2021, and the outcomes were compared to the preceding 5 years and a control ward. The alert identified 324 children and 596 febrile episodes. Vital signs measurement adherence increased from 42.7% to >90% in 2 months. A nurse evaluated 86.4% of episodes, and a physician evaluated 83.0% of these. Paediatric intensive care unit (PICU) admission rates were lower in the intervention period vs. the pre-intervention period vs. the control ward (4.6% vs. 5.6% vs. 6.0%, respectively); the median PICU length of stay was shorter in the intervention vs. the control ward [2.0 (IQR 1, 4) vs. 5.5 (IQR 2, 7), respectively]. These differences were not statistically significant. During the intervention period, the adherence to vital signs measurements reached the goal of >90%. The alert system prompted an evaluation by caregivers and management according to the protocol. Further monitoring is needed to improve outcomes.

The intentions of Israeli nurses attending university programs to receive seasonal influenza vaccination.

BACKGROUND: Seasonal influenza vaccination (SIV) among medical personnel is a key factor in preventive medicine and patient safety. OBJECTIVE: To identify social-cognitive predictors of Israeli Registered Nurses' (RNs) intentions to receive SIV utilizing the Theory of Planned Behaviour (TPB) model, and to assess its predictive validity. METHODS: A cross-sectional study was conducted. A structured, self-reported, anonymous, 43-item questionnaire, based on an extended version of the TPB, was administered to 80 nurses attending Master's or Bachelor in Nursing degrees curriculums. A multivariable regression analysis was used to determine independent predictors of influenza vaccination compliance among nurses. RESULTS: A multivariable regression analysis indicated that two TPB model variables: control beliefs (ß = 0.277, P < 0.01) and attitudes regarding SIV (ß = 0.441, P < 0.001) contributed significantly to the prediction of RNs' SIV intentions. CONCLUSIONS: The results of the current study indicate that the TPB may partially explain the intentions of RNs to receive SIV and illustrates the importance of beliefs and attitudes to health-related behaviours. It may direct us to seek interventions focusing on strengthening beliefs and attitudes to achieve higher intention levels to get vaccinated and thus affect the desired behaviours.