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PubMed2026

Evaluation of Physical and Mental Workload and Transfusion Time in Trauma Resuscitation.

BACKGROUND: Trauma resuscitation is time sensitive and complex. Whole blood (WB) and blood components are standard treatments for trauma related hemorrhage, yet their nursing workload and transfusion time have not been well evaluated. PURPOSE: To assess feasibility of a simulation-based crossover trial and obtain preliminary estimates comparing nursing workload and transfusion completion time between WB and blood component administration. METHODS: A randomized crossover pilot study using in situ simulation was conducted with experienced trauma nurses. Time-motion analysis measured transfusion completion time, and the National Aeronautical and Space Administration Task Load Index assessed workload domains. RESULTS: Strong feasibility was demonstrated across recruitment, retention, adherence, and completion. WB was associated with significantly shorter transfusion time, lower overall workload and mental demand, less effort, and better perceived performance. CONCLUSIONS: These findings support the feasibility and justify a fully powered trial. WB may improve resuscitation efficiency and reduce cognitive burden, with potential implications for patient outcomes and nursing workflow.

Humans↗
PubMed2026

Alarms and alarm management with automated versus conventional ventilation in neurocritical care patients.

INTRODUCTION: False or clinically irrelevant alarms are a major driver of ICU alarm fatigue and nursing workload. Ventilator alarms make up a large share, and although automated ventilation modes can reduce manual adjustments, their effect on alarm burden is still unclear. This issue can be particularly relevant in neurocritical care patients, where precise ventilator and alarm management is imperative for patient safety. OBJECTIVES: This explorative post hoc analysis of a randomized clinical trial compared alarm frequency and management between automated ventilation and conventional ventilation in neurocritical care patients. METHODS: Ventilator alarms and manual ventilator changes were captured continuously from the ventilator for up to 24 h per patient. The primary endpoint was a composite of workload-relevant alarms; with alarm management interventions at the ventilator as a key secondary outcome. Additional endpoints included redundant alarms, alarm duration and ventilator management. RESULTS: 13 patients received automated ventilation and 24 received conventional ventilation. No difference was observed in workload-relevant alarm frequency between automated and conventional ventilation (3.28 [2.87 to 4.30] vs 3.73 [1.66 to 7.33] alarms per hour; P = 0.81), while alarm management interventions at the ventilator were lower with automated ventilation (0.14 [0.10 to 0.15] vs 0.21 [0.17 to 0.31] interventions per hour; P = 0.01). Other alarm frequencies, duration of alarms and ventilator management were similar. CONCLUSIONS: In this exploratory post hoc analysis of a randomized clinical trial in neurocritical care patients during the early phase of mechanical ventilation, automated ventilation did not reduce the frequency of total or workload-relevant alarms, nor their duration, but was associated with fewer alarm management interventions compared to conventional ventilation. IMPLICATIONS FOR CLINICAL PRACTICE: Automated ventilation may not reduce alarm frequency in neurocritical care patients, but the observed reduction in alarm-related bedside interventions suggests a potential benefit for nursing workload.

Humans↗
PubMed2026

Global prevalence and associated factors of turnover intention among intensive care nurses: A systematic review and meta-analysis.

OBJECTIVES: To estimate the global prevalence of two distinct turnover intentions among intensive care unit (ICU) nurses-intention to leave the ICU and intention to leave the nursing profession-identify significant sources of heterogeneity, and synthesise associated psychosocial factors. METHODS: Ten databases were systematically searched from inception to September 28, 2025. Two reviewers independently conducted study selection, data extraction, and quality appraisal using Joanna Briggs Institute checklists. Random-effects meta-analyses were performed to estimate pooled prevalence and associated factors. Subgroup and meta-regression analyses explored potential sources of heterogeneity. Associated factors were pooled as odds ratios (ORs) and interpreted within an integrated Job Demands-Resources and Theory of Planned Behavior framework. RESULTS: Forty-six studies published between 2007 and 2025, involving 39,246 ICU nurses, were included. The pooled prevalence was 30.7% for intention to leave the ICU and 27.5% for intention to leave the nursing profession. Significant sources of heterogeneity included ICU type, geographic region, publication year, study design, measurement tool, and sampling method. Depression, burnout, high workload, and unsafe patient-to-nurse ratios were associated with increased turnover intention, whereas positive work environments, perceived organisational support, and nursing competence were protective factors. No significant publication bias was detected. CONCLUSIONS: Turnover intention affects approximately one-third of ICU nurses globally and varies across clinical and geographical contexts. Excessive workload, inadequate organisational support, and unfavourable work environments appear to be important contributors to turnover intention among ICU nurses. IMPLICATIONS FOR CLINICAL PRACTICE: Strategies to reduce turnover intention among ICU nurses should focus on reducing excessive workload, improving staffing conditions, strengthening organisational support, and fostering positive work environments. Promoting supportive and sustainable ICU work environments may help improve nurse retention and maintain the quality of critical care services.

Humans↗
PubMed2026

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan® for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans↗
PubMed2026

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans↗