Development of process control methodology for tracking the quality and safety of pain, agitation and sedation management in critical care units

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

Responsiveness of the frontal EMG for monitoring the sedation state of critically ill patients.

Background. Excessive sedation is associated with adverse patient outcomes during critical illness, and a validated monitoring technology could improve care. We developed a novel method, the responsiveness index (RI) of the frontal EMG. We compared RI data with Ramsay clinical sedation assessments in general and cardiac intensive care unit (ICU) patients. Methods. We developed the algorithm by iterative analysis of detailed observational data in 30 medical–surgical ICU patients and described its performance in this cohort and 15 patients recovering from scheduled cardiac surgery. Continuous EMG data were collected via frontal electrodes and RI data compared with modified Ramsay sedation state assessments recorded regularly by a blinded trained observer. RI performance was compared with EntropyTM across Ramsay categories to assess validity. Results. RI correlated well with the Ramsay category, especially for the cardiac surgery cohort (general ICU patients r¼0.55; cardiac surgery patients r¼0.85, both P,0.0001). Discrimination across all Ramsay categories was reasonable in the general ICU patient cohort [PK¼0.74 (SEM 0.02)] and excellent in the cardiac surgery cohort [PK¼0.92 (0.02)]. Discrimination between ‘lighter’ vs ‘deeper’ (Ramsay 1–3 vs 4–6) was good for general ICU patients [PK¼0.80 (0.02)] and excellent for cardiac surgery patients [PK¼0.96 (0.02)]. Performance was significantly better than EntropyTM. Examination of individual cases suggested good face validity. Conclusions. RI of the frontal EMG has promise as a continuous sedation state monitor in critically ill patients. Further investigation to determine its utility in ICU decision-making is warranted.