TAILR (Nursing-Sensitive Events and Their Association With Individual Nurse Staffing Levels) Project: Protocol for an International Longitudinal Multicenter Study.

BACKGROUND: Nursing-sensitive events (NSEs) are common, accounting for up to 77% of adverse events in hospitalized patients (eg, fall-related harm, pressure ulcers, and health care-associated infections). NSEs lead to adverse patient outcomes and impose an economic burden on hospitals due to increased medical costs through a prolonged hospital stay and additional medical procedures. To reduce NSEs and ensure high-quality nursing care, appropriate nurse staffing levels are needed. Although the link between nurse staffing and NSEs has been described in many studies, appropriate nurse staffing levels are lacking. Existing studies describe constant staffing exposure at the unit or hospital level without assessing patient-level exposure to nurse staffing during the hospital stay. Few studies have assessed nurse staffing and patient outcomes using a single-center longitudinal design, with limited generalizability. There is a need for multicenter longitudinal studies with improved potential for generalizing the association between individual nurse staffing levels and NSEs. OBJECTIVE: This study aimed (1) to determine the prevalence, preventability, type, and severity of NSEs; (2) to describe individual patient-level nurse staffing exposure across hospitals; (3) to assess the effect of nurse staffing on NSEs in patients; and (4) to identify thresholds of safe nurse staffing levels and test them against NSEs in hospitalized patients. METHODS: This international multicenter study uses a longitudinal and observational research design; it involves 4 countries (Switzerland, Sweden, Germany, and Iran), with participation from 14 hospitals and 61 medical, surgery, and mixed units. The 16-week observation period will collect NSEs using systematic retrospective record reviews. A total of 3680 patient admissions will be reviewed, with 60 randomly selected admissions per unit. To be included, patients must have been hospitalized for at least 48 hours. Nurse staffing data (ie, the number of nurses and their education level) will be collected daily for each shift to assess the association between NSEs and individual nurse staffing levels. Additionally, hospital data (ie, type, teaching status, and ownership) and unit data (ie, service line and number of beds) will be collected. RESULTS: As of January 2024, the verification process for the plausibility and comprehensibility of patients' and nurse staffing data is underway across all 4 countries. Data analyses are planned to be completed by spring 2024, with the first results expected to be published in late 2024. CONCLUSIONS: This study will provide comprehensive information on NSEs, including their prevalence, preventability, type, and severity, across countries. Moreover, it seeks to enhance understanding of NSE mechanisms and the potential impact of nurse staffing on these events. We will evaluate within- and between-hospital variability to identify productive strategies to ensure safe nurse staffing levels, thereby reducing NSEs in hospitalized patients. The TAILR (Nursing-Sensitive Events and Their Association With Individual Nurse Staffing Levels) study will focus on the optimization of scarce staffing resources. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56262.

Identifying neonatal adverse events in preterm and term infants using a paediatric trigger tool.

AIM: To explore the incidence and characteristics of inpatient neonatal adverse events in a Swedish setting. METHODS: A retrospective record review, using a trigger tool, performed by registered nurses and a neonatologist, at a University Hospital. The identified adverse events were categorised by, for example, preventability, severity and time of occurrence. RESULTS: A random selection of 150 admissions representing 3531 patient days were reviewed (mean [SD] birthweight 2620 [1120]g). Three hundred and sixty adverse events were identified in 78 (52.0%) infants, and 305 (84.7%) of these were assessed as being preventable. The overall adverse event rate was 240 per 100 admissions and 102.0 per 1000 patient days. Preterm infants had a higher rate than term infants (353 versus 79 per 100 admissions, p = 0.001); however, with regard to the length of stay, the rates were similar. Most adverse events were temporary and less severe (n = 338/360, 93.9%) and the most common type involved harm to skin, tissue or blood vessels (n = 163/360, 45.3%). Forty percent (n = 145) of adverse events occurred within the first week of admission. CONCLUSION: Adverse events were common in neonatal care, and many occurred during the first days of treatment. Characterisation of adverse events may provide focus areas for improvements in patient safety.

Incidence and characteristics of adverse events in paediatric inpatient care: a systematic review and meta-analysis.

BACKGROUND: Adverse events (AEs) cause suffering for hospitalised children, a fragile patient group where the delivery of adequate timely care is of great importance. OBJECTIVE: To report the incidence and characteristics of AEs, in paediatric inpatient care, as detected with the Global Trigger Tool (GTT), the Trigger Tool (TT) or the Harvard Medical Practice Study (HMPS) method. METHOD: MEDLINE, Embase, Web of Science and Google Scholar were searched from inception to June 2021, without language restrictions. Studies using manual record review were included if paediatric data were reported separately. We excluded studies reporting: AEs for a specific disease/diagnosis/treatment/procedure, or deceased patients; study protocols with no AE outcomes; conference abstracts, editorials and systematic reviews; clinical incident reports as the primary data source; and studies focusing on specific AEs only. Methodological risk of bias was assessed using a tool based on the Quality Assessment Tool for Diagnostic Accuracy Studies 2. Primary outcome was the percentage of admissions with ≥1 AEs. All statistical analyses were stratified by record review methodology (GTT/TT or HMPS) and by type of population. Meta-analyses, applying random-effects models, were carried out. The variability of the pooled estimates was characterised by 95% prediction intervals (PIs). RESULTS: We included 32 studies from 44 publications, conducted in 15 countries totalling 33 873 paediatric admissions. The total number of AEs identified was 8577. The most common types of AEs were nosocomial infections (range, 6.8%-59.6%) for the general care population and pulmonary-related (10.5%-36.7%) for intensive care. The reported incidence rates were highly heterogeneous. The PIs for the primary outcome were 3.8%-53.8% and 6.9%-91.6% for GTT/TT studies (general and intensive care population). The equivalent PI was 0.3%-33.7% for HMPS studies (general care). The PIs for preventable AEs were 7.4%-96.2% and 4.5%-98.9% for GTT/TT studies (general and intensive care population) and 10.4%-91.8% for HMPS studies (general care). The quality assessment indicated several methodological concerns regarding the included studies. CONCLUSION: The reported incidence of AEs is highly variable in paediatric inpatient care research, and it is not possible to estimate a reliable single rate. Poor reporting standards and methodological differences hinder the comparison of study results.