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To quantify how specific patient-level characteristics influence the actual amount of mobilisation received during ICU care, thereby identifying key predictors to support individualised mobilisation strategies.
A prospective observational study was conducted in four tertiary hospitals among a convenience sample of 141 critically ill patients from July to November 2023. Data on mobilisation and patient characteristics were collected using standardised data collection tools, including a mobilisation log and a demographic information sheet. Data were analysed using non-parametric tests, Spearman correlation analysis, and multivariate regression to examine associations between early mobilisation and patient-related factors.
Males and surgical patients engaged in more activity (p < 0.001). Muscle strength (r = 0.568, p < 0.001) and haemoglobin levels (r = 0.207, p = 0.014) were positively associated with mobilisation, while higher disease severity (r = −0.321, p < 0.001) and greater pain (r = −0.284, p < 0.001) were linked to reduced activity. Muscle strength, disease severity, surgical status, and sex were independent predictors, explaining 32.5% of the variance.
Early mobilisation in the ICU is influenced by various patient-related factors. Protocols should be tailored to individual patient profiles to enhance outcomes.
This study provides guidance for ICU clinicians to develop targeted mobilisation strategies that consider patients' specific clinical profiles. Tailored approaches may help optimise early mobilisation practices and patient outcomes.
To compare contextual factors influencing discharge practices in three intensive care units (ICUs).
A prospective observational study.
Data were collected using a discharge process report form (DPRF) between May and September 2023. Descriptive statistics were performed to analyse demographic and clinical data. One-way analysis of variance (ANOVA) was used to test the time interval differences among the three sites.
Overall, 69 patients' discharge processes were observed. Among them, 41 (59%) experienced discharge delay, and 1 in 5 patients experienced after-hours discharge. There were statistically significant differences in mean hours in various time intervals during the discharge processes among the three sites. Patients in Hospital C waited the longest time (mean = 31.9 h) for the ward bed to be ready after the bed was requested and for being eventually discharged after ICU nurses to get them ready for discharge (mean = 26.7 h) compared to Hospital A and Hospital B.
We found that discharge delay and after-hours discharge were common and there were significant differences in mean hours of various time intervals during the discharge processes occurred among the three sites. The influence of contextual factors in different hospitals/ICU needs to be considered to improve the ICU discharge process.
Researchers and clinicians should consider targeted context-specific interventions and strategies to optimise patient discharge process from ICUs.
The study findings will inform the development of tailored interventions to reduce the discharge delay and after-hours discharge and, in turn, improve the quality and safety of patient care and health service efficiency.
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Patients' discharge processes were observed, and consumer representatives were involved in the study design.
FreshRSS 