Journal
CRITICAL CARE MEDICINE
Volume 44, Issue 3, Pages 564-574Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/CCM.0000000000001463
Keywords
intensive care units; quality improvement; sedation; pain management; critical care; process measures; conscious
Categories
Funding
- Scottish Chief Scientist's Office [CZH/3/3]
- GE Healthcare
- Scottish Chief Scientists Office (CSO)
- Wellcome Trust
- Medical Research Council, United Kingdom
- Engineering and Physical Sciences Research Council, United Kingdom
- Technology Strategy Board, United Kingdom
- Health Technology Assessment Agency, United Kingdom
- CSO
- NHS Lothian RD Department
- University of Edinburgh
- Scottish CSO
- NHS Lothian via the Edinburgh Health Services Research Unit
- Chief Scientist Office [CZH/3/3] Funding Source: researchfish
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Objective: To develop sedation, pain, and agitation quality measures using process control methodology and evaluate their properties in clinical practice. Design: A Sedation Quality Assessment Tool was developed and validated to capture data for 12-hour periods of nursing care. Domains included pain/discomfort and sedation-agitation behaviors; sedative, analgesic, and neuromuscular blocking drug administration; ventilation status; and conditions potentially justifying deep sedation. Predefined sedation-related adverse events were recorded daily. Using an iterative process, algorithms were developed to describe the proportion of care periods with poor limb relaxation, poor ventilator synchronization, unnecessary deep sedation, agitation, and an overall optimum sedation metric. Proportion charts described processes over time (2 monthly intervals) for each ICU. The numbers of patients treated between sedation-related adverse events were described with G charts. Automated algorithms generated charts for 12 months of sequential data. Mean values for each process were calculated, and variation within and between ICUs explored qualitatively. Setting: Eight Scottish ICUs over a 12-month period. Patients: Mechanically ventilated patients. Interventions: None. Measurements and Main Results: The Sedation Quality Assessment Tool agitation-sedation domains correlated with the Richmond Sedation Agitation Scale score (Spearman rho = 0.75) and were reliable in clinician-clinician (weighted kappa; kappa = 0.66) and clinician-researcher (kappa = 0.82) comparisons. The limb movement domain had fair correlation with Behavioral Pain Scale (rho = 0.24) and was reliable in clinician-clinician (kappa = 0.58) and clinician-researcher (kappa = 0.45) comparisons. Ventilator synchronization correlated with Behavioral Pain Scale (rho = 0.54), and reliability in clinician-clinician (kappa = 0.29) and clinician-researcher (kappa = 0.42) comparisons was fair-moderate. Eight hundred twenty-five patients were enrolled (range, 59-235 across ICUs), providing 12,385 care periods for evaluation (range 655-3,481 across ICUs). The mean proportion of care periods with each quality metric varied between ICUs: excessive sedation 12-38%; agitation 4-17%; poor relaxation 13-21%; poor ventilator synchronization 8-17%; and overall optimum sedation 45-70%. Mean adverse event intervals ranged from 1.5 to 10.3 patients treated. The quality measures appeared relatively stable during the observation period. Conclusions: Process control methodology can be used to simultaneously monitor multiple aspects of pain-sedation-agitation management within ICUs. Variation within and between ICUs could be used as triggers to explore practice variation, improve quality, and monitor this over time.
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