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Sepsis is a major cause of death both globally and in the United States. Early identification and treatment of sepsis are crucial for improving patient outcomes. International guidelines recommend hospital sepsis screening programmes, which are commonly implemented in the electronic health record (EHR) as an interruptive sepsis screening alert based on systemic inflammatory response syndrome (SIRS) criteria. Despite widespread use, it is unknown whether these sepsis screening and alert tools improve the delivery of high-quality sepsis care.
The Sepsis Electronic Prompting for Timely Intervention and Care (SEPTIC) master protocol will study two distinct populations in separate trials: emergency department (ED) patients (SEPTIC-ED) and inpatients (SEPTIC-IP). The SEPTIC trials are pragmatic, multicentre, blinded, randomised controlled trials, with equal allocation to compare four SIRS-based sepsis screening alert groups: no alerts (control), nurse alerts only, prescribing clinician alerts only, or nurse and prescribing clinician alerts. Randomisation will be at the patient level. SEPTIC will be performed at eight acute-care hospitals in the greater New York City area and enrol patients at least 18 years old. The primary outcome is the percentage of patients with completion of a modified Surviving Sepsis Campaign (SSC) hour-1 bundle within 3 hours of the first SIRS alert. Secondary outcomes include time from first alert to completion of a modified SSC hour-1 bundle, time from first alert to individual bundle component order and completion, intensive care unit (ICU) transfer, hospital discharge disposition, inpatient mortality at 90 days, positive blood cultures (bacteraemia), adverse antibiotic events, sepsis diagnoses and septic shock diagnoses.
Ethics approval was obtained from the Columbia University Institutional Review Board (IRB) serving as a single IRB. Results will be disseminated in peer-reviewed journal(s), scientific meeting(s) and via social media.
ClinicalTrials.gov: NCT06117605 and
In order to be positioned to address the increasing strain of burnout and worsening nurse shortage, a better understanding of factors that contribute to nursing workload is required. This study aims to examine the difference between order-based and clinically perceived nursing workloads and to quantify factors that contribute to a higher clinically perceived workload.
A retrospective cohort study was used on an observational dataset.
We combined patient flow, nurse staffing and assignment, and workload intensity data and used multivariate linear regression to analyze how various shift, patient, and nurse-level factors, beyond order-based workload, affect nurses' clinically perceived workload.
Among 53% of our samples, the clinically perceived workload is higher than the order-based workload. Factors associated with a higher clinically perceived workload include weekend or night shifts, shifts with a higher census, patients within the first 24 h of admission, and male patients.
The order-based workload measures tended to underestimate nurses' clinically perceived workload. We identified and quantified factors that contribute to a higher clinically perceived workload, discussed the potential mechanisms as to how these factors affect the clinically perceived workload, and proposed targeted interventions to better manage nursing workload.
By identifying factors associated with a high clinically perceived workload, the nurse manager can provide appropriate interventions to lighten nursing workload, which may further reduce the risk of nurse burnout and shortage.
FreshRSS 