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The overall CR per bedside was poor particularly with indication (2).
The frequency of hand disinfection events was expressed in two ways: the daily median [interquartile range (IQR)] number of hand disinfection events per bedside; and the daily median (IQR) number of hand disinfection events per healthcare worker.
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Multivariate regression modeling revealed that minutes at the bedside per patient was negatively associated with pediatrics (-2.77 adjusted bedside minutes; 95% CI -4.61 to -0.93; p<.001) but positively associated with the number of non-physician participants (0.12 adjusted bedside minutes per non physician participant; 95% CI 0.07 to 0.17; p = <.001).
Assessment performed per shift by bedside nurses.
Multivariate regression modeling revealed that minutes at the bedside per patient was negatively associated with pediatrics (−2.77 adjusted bedside minutes; 95% CI −4.61 to −0.93; p<.001) but positively associated with the number of non-physician participants (0.12 adjusted bedside minutes per non physician participant; 95% CI 0.07 to 0.17; p = <.001).
All interventions took place at the patient's bedside per visit and were recorded in a clinical form.
During their on-call day, in addition to five hours per week of bedside teaching sessions and small group interactive sessions, students clerk all patients admitted then present and discuss the case with the clinical team.
The average amount of time spent at the bedside on a per patient basis (4.1 minutes for internal medicine, 1.9 minutes for pediatrics) was significantly smaller for pediatrics.
Sedation was scored using the Richmond Agitation-Sedation Scale (RASS) and delirium was assessed using the Confusion Assessment Method (CAM-ICU) per shift by the bedside nurses, if they were responsive to verbal commands (RASS score of −3 or lighter level of sedation).
The nursing workload [measured using the Therapeutic Intervention Scoring System (TISS-76)] for all patients in the ICU during each day to average number of bedside nurses per shift on that day (workload/nurse) ratio, severity of illness (using Acute Physiology and Chronic Health Evaluation III) and hospital survival were analysed using net-benefit regression methodology and logistic regression.
To gauge the predictors of patient care and educational aspects of rounds, we performed multivariable regression analysis using a generalized estimating equation (GEE) methodology for two outcome variables: bedside minutes per patient and education minutes.
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