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Delirium and sedation recognition using validated instruments: reliability of bedside intensive care unit nursing
Eduard E Vasilevskis1, Alessandro Morandi, Leanne Boehm
1Geriatric Research, Education and Clinical Center, Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, Tennessee, USA. eduard.vasilevskis@vanderbilt.edu
Objectives:
To describe the reliability and sustainability of delirium and sedation measurements of bedside intensive care unit (ICU) nurses.
Design:
Prospective cohort study.
Setting:
A tertiary care academic medical center.
Participants:
Five hundred ten ICU patients from 2007 to 2010; 627 bedside nurses.
Measurements:
Bedside nurses and well-trained reference-rater research nurses independently measured delirium and sedation levels in routine care. Bedside nurses were instructed to use the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) every 12 hours to measure delirium and the Richmond Agitation-Sedation Scale (RASS) every 4 hours to measure sedation. CAM-ICU and RASS assessment agreement were computed using weighted kappa statistics across the entire population and subgroups (e.g., ICU type). Sensitivity and specificity of bedside nurse identification of delirium were calculated to understand sources of discordance.
Results:
Six thousand one hundred ninety-eight CAM-ICU and 6,880 RASS measurement pairs obtained on 3,846 patient-days. For CAM-ICU measurements, agreement between bedside and research nurses was substantial (weighted kappa = 0.67, 95% confidence interval (CI) = 0.66-0.70) and stable over 3 years of data collection. RASS measures also demonstrated substantial agreement (weighted kappa = 0.66, 95% CI = 0.64-0.68), which was stable across all years of data collection. The sensitivity of delirium nurse assessments was 0.81 (95% CI = 0.78-0.83), and the specificity was 0.81 (95% CI = 0.78-0.85).
Conclusion:
Bedside nurse measurements of delirium and sedation are sustainable and reliable sources of information. These measures can be used for clinical decision-making, quality improvement, and quality measurement activities.
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