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 ρ = 0.75) and were reliable in clinician-clinician (weighted kappa; κ = 0.66) and clinician-researcher (κ = 0.82) comparisons. The limb movement domain had fair correlation with Behavioral Pain Scale (ρ = 0.24) and was reliable in clinician-clinician (κ = 0.58) and clinician-researcher (κ = 0.45) comparisons. Ventilator synchronization correlated with Behavioral Pain Scale (ρ = 0.54), and reliability in clinician-clinician (κ = 0.29) and clinician-researcher (κ = 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.

A randomized controlled proof-of-concept trial of early sedation management using Responsiveness Index monitoring in mechanically ventilated critically ill patients.

INTRODUCTION: Deep sedation is associated with adverse patient outcomes. We recently described a novel sedation-monitoring technology, the Responsiveness Index (RI), which quantifies patient arousal using processed frontal facial EMG data. We explored the potential effectiveness and safety of continuous RI monitoring during early intensive care unit (ICU) care as a nurse decision-support tool. METHODS: In a parallel-group controlled single centre proof of concept trial, patients requiring mechanical ventilation and sedation were randomized via sequential sealed envelopes following ICU admission. Control group patients received hourly clinical sedation assessment and daily sedation holds; the RI monitor was connected but data were concealed from clinical staff. The intervention group received control group care, but RI monitoring was visible and nurses were asked to adjust sedation to maintain patients with an RI>20 whenever possible. Traffic-light colour coding (RI<20, Red; 20-40, Amber; >40, Green) simplified decision-making. The intervention lasted up to 48 hours. Sixteen nurses were interviewed to explore their views of the novel technology. RESULTS: We analysed 74 patients treated per protocol (36 intervention; 38 control). The proportion of patients with RI<20 was identical at the start of monitoring (54% both groups). Overall, the proportion of time with RI<20 trended to lower values for the intervention group (median 16% (1-3rd quartile 8-30%) versus 33% (10-54%); P = 0.08); sedation and analgesic use was similar. A post hoc analysis restricted to patients with RI<20 when monitoring started, found intervention patients spent less time with low RI value (16% (11-45%) versus 51% (33-72%); P = 0.02), cumulative propofol use trended to lower values (median 1090 mg versus 2390 mg; P = 0.14), and cumulative alfentanil use was lower (21.2 mg versus 32.3 mg; P = 0.01). RASS scores were similar for both groups. Sedation related adverse event rates were similar (7/36 versus 5/38). Similar proportions of patients had sedation holds (83% versus 87 %) and were extubated (47% versus 44%) during the intervention period. Nurses valued the objective visible data trends and simple colour prompts, and found RI monitoring a useful adjunct to existing practice. CONCLUSIONS: RI monitoring was safe and acceptable. Data suggested potential to modify sedation decision-making. Larger trials are justified to explore effects on patient-centred outcomes. TRIAL REGISTRATION: NCT01361230 (registered April 19, 2010).

'Targeting' sedation: the lived experience of the intensive care nurse.

AIMS AND OBJECTIVES: To discuss the findings from a phenomenological study that provides insights into the intensive care nurses' 'world' following changes in the sedation management of patients in an intensive care unit. BACKGROUND: Intensive care sedation practices have undergone significant changes. Patients, where possible, are now managed on lighter levels of sedation, often achieved through the performance of sedation holds (SHs). The performance of SHs is normally carried out by the bedside nurse but compliance is reported to be poor. There has been little exploration of the nurses' experiences of these changes and the implications of SHs and subsequent wakefulness on their delivery of care. DESIGN: Following ethical approval, 16 intensive care nurses, experienced and inexperienced, from within a general intensive care unit. METHODS: A Heideggerian phenomenological approach was used. Data collection consisted of interviews guided by an aide memoir and a framework adapted from Van Manen informed the analysis. RESULTS: The findings reveal new insights into the world of the intensive care nurse in the light of the changes to sedation management. They demonstrate that there have been unforeseen outcomes from well-intentioned initiatives to improve the quality of patients' care. There were implications from the changes introduced for the nurses care delivery. The main themes that emerged were 'working priorities' and 'unintended consequences', in turn revealing embedded tensions between evidence-based targets and holistic care. CONCLUSIONS: Intensive care nurses find that the current approach to the changes in sedation management can threaten their professional obligation and personal desire to provide holistic care. The 'targeted' approach by healthcare organisations is perceived to militate against the patient-centred care they want to deliver. RELEVANCE TO CLINICAL PRACTICE: Sedation management is complex and needs further consideration particularly the potential constraints 'target-led' care has on nursing practice.

Reducing ventilator-associated pneumonia in intensive care: impact of implementing a care bundle.

OBJECTIVES: Ventilator-associated pneumonia is the most common intensive care unit-acquired infection. Although there is widespread consensus that evidenced-based interventions reduce the risk of ventilator-associated pneumonia, controversy has surrounded the importance of implementing them as a "bundle" of care. This study aimed to determine the effects of implementing such a bundle while controlling for potential confounding variables seen in similar studies. DESIGN: A before-and-after study conducted within the context of an existing, independent, infection surveillance program. SETTING: An 18-bed, mixed medical-surgical teaching hospital intensive care unit. PATIENTS: All patients admitted to intensive care for 48 hrs or more during the periods before and after intervention. INTERVENTIONS: A four-element ventilator-associated pneumonia prevention bundle, consisting of head-of-bed elevation, oral chlorhexidine gel, sedation holds, and a weaning protocol implemented as part of the Scottish Patient Safety Program using Institute of Health Care Improvement methods. MEASUREMENTS AND MAIN RESULTS: Compliance with head-of-bed elevation and chlorhexidine gel were 95%-100%; documented compliance with "wake and wean" elements was 70%, giving overall bundle compliance rates of 70%. Compared to the preintervention period, there was a significant reduction in ventilator-associated pneumonia in the postintervention period (32 cases per 1,000 ventilator days to 12 cases per 1,000 ventilator days; p<.001). Statistical process control charts showed the decrease was most marked after bundle implementation. Patient cohorts staying ≥6 and ≥14 days had greater reduction in ventilator-associated pneumonia acquisition and also had reduced antibiotic use (reduced by 1 and 3 days; p=.008/.007, respectively). Rates of methicillin-resistant Staphylococcus aureus acquisition also decreased (10% to 3.6%; p<.001). CONCLUSIONS: Implementation of a ventilator-associated pneumonia prevention bundle was associated with a statistically significant reduction in ventilator-associated pneumonia, which had not been achieved with earlier ad hoc ventilator-associated pneumonia prevention guidelines in our unit. This occurred despite an inability to meet bundle compliance targets of 95% for all elements. Our data support the systematic approach to achieving high rates of process compliance and suggest systematic introduction can decrease both infection incidence and antibiotic use, especially for patients requiring longer duration of ventilation.

Rationale, design and methodology of a trial evaluating three strategies designed to improve sedation quality in intensive care units (DESIST study).

OBJECTIVES: To describe the rationale, design and methodology for a trial of three novel interventions developed to improve sedation-analgesia quality in adult intensive care units (ICUs). PARTICIPANTS AND SETTING: 8 clusters, each a Scottish ICU. All mechanically ventilated sedated patients were potentially eligible for inclusion in data analysis. DESIGN: Cluster randomised design in 8 ICUs, with ICUs randomised after 45 weeks baseline data collection to implement one of four intervention combinations: a web-based educational programme (2 ICUs); education plus regular sedation quality feedback using process control charts (2 ICUs); education plus a novel sedation monitoring technology (2 ICUs); or all three interventions. ICUs measured sedation-analgesia quality, relevant drug use and clinical outcomes, during a 45-week preintervention and 45-week postintervention period separated by an 8-week implementation period. The intended sample size was >100 patients per site per study period. MAIN OUTCOME MEASURES: The primary outcome was the proportion of 12 h care periods with optimum sedation-analgesia, defined as the absence of agitation, unnecessary deep sedation, poor relaxation and poor ventilator synchronisation. Secondary outcomes were proportions of care periods with each of these four components of optimum sedation and rates of sedation-related adverse events. Sedative and analgesic drug use, and ICU and hospital outcomes were also measured. ANALYTIC APPROACH: Multilevel generalised linear regression mixed models will explore the effects of each intervention taking clustering into account, and adjusting for age, gender and APACHE II score. Sedation-analgesia quality outcomes will be explored at ICU level and individual patient level. A process evaluation using mixed methods including quantitative description of intervention implementation, focus groups and direct observation will provide explanatory information regarding any effects observed. CONCLUSIONS: The DESIST study uses a novel design to provide system-level evaluation of three contrasting complex interventions on sedation-analgesia quality. Recruitment is complete and analysis ongoing. TRIAL REGISTRATION NUMBER: NCT01634451.

Staff education, regular sedation and analgesia quality feedback, and a sedation monitoring technology for improving sedation and analgesia quality for critically ill, mechanically ventilated patients: a cluster randomised trial.

BACKGROUND: Optimal sedation of patients in intensive care units (ICUs) requires the avoidance of pain, agitation, and unnecessary deep sedation, but these outcomes are challenging to achieve. Excessive sedation can prolong ICU stay, whereas light sedation can increase pain and frightening memories, which are commonly recalled by ICU survivors. We aimed to assess the effectiveness of three interventions to improve sedation and analgesia quality: an online education programme; regular feedback of sedation-analgesia quality data; and use of a novel sedation-monitoring technology (the Responsiveness Index [RI]). METHODS: We did a cluster randomised trial in eight ICUs, which were randomly allocated to receive education alone (two ICUs), education plus sedation-analgesia quality feedback (two ICUs), education plus RI monitoring technology (two ICUs), or all three interventions (two ICUs). Randomisation was done with computer-generated random permuted blocks, stratified according to recruitment start date. A 45 week baseline period was followed by a 45 week intervention period, separated by an 8 week implementation period in which the interventions were introduced. ICU and research staff were not masked to study group assignment during the intervention period. All mechanically ventilated patients were potentially eligible. We assessed patients' sedation-analgesia quality for each 12 h period of nursing care, and sedation-related adverse events daily. Our primary outcome was the proportion of care periods with optimal sedation-analgesia, defined as being free from excessive sedation, agitation, poor limb relaxation, and poor ventilator synchronisation. Analysis used multilevel generalised linear mixed modelling to explore intervention effects in a single model taking clustering and patient-level factors into account. A concurrent mixed-methods process evaluation was undertaken to help understand the trial findings. The trial is registered with ClinicalTrials.gov, number NCT01634451. FINDINGS: Between June 1, 2012, and Dec 31, 2014, we included 881 patients (9187 care periods) during the baseline period and 591 patients (6947 care periods) during the intervention period. During the baseline period, optimal sedation-analgesia was present for 5150 (56%) care periods. We found a significant improvement in optimal sedation-analgesia with RI monitoring (odds ratio [OR] 1·44 [95% CI 1·07-1·95]; p=0·017), which was mainly due to increased periods free from excessive sedation (OR 1·59 [1·09-2·31]) and poor ventilator synchronisation (OR 1·55 [1·05-2·30]). However, more patients experienced sedation-related adverse events (OR 1·91 [1·02-3·58]). We found no improvement in overall optimal sedation-analgesia with education (OR 1·13 [95% CI 0·86-1·48]), but fewer patients experienced sedation-related adverse events (OR 0·56 [0·32-0·99]). The sedation-analgesia quality data feedback did not improve quality (OR 0·74 [95% CI 0·54-1·00]) or sedation-related adverse events (OR 1·15 [0·61-2·15]). The process evaluation suggested many clinicians found the RI monitoring useful, but it was often not used for decision making as intended. Education was valued and considered useful by staff. By contrast, sedation-analgesia quality feedback was poorly understood and thought to lack relevance to bedside nursing practice. INTERPRETATION: Combination of RI monitoring and online education has the potential to improve sedation-analgesia quality and patient safety in mechanically ventilated ICU patients. The RI monitoring seemed to improve sedation-analgesia quality, but inconsistent adoption by bedside nurses limited its impact. The online education programme resulted in a clinically relevant improvement in patient safety and was valued by nurses, but any changes to behaviours did not seem to alter other measures of sedation-analgesia quality. Providing sedation-analgesia quality feedback to ICUs did not appear to improve any quality metrics, probably because staff did not think it relevant to bedside practice. FUNDING: Chief Scientist Office, Scotland; GE Healthcare.

An evaluation of the validity and potential utility of facial electromyelogram Responsiveness Index for sedation monitoring in critically ill patients.

PURPOSE: The purpose of this study is to explore the validity of a novel sedation monitoring technology based on facial electromyelography (EMG) in sedated critically ill patients. MATERIALS AND METHODS: The Responsiveness Index (RI) integrates the preceding 60 minutes of facial EMG data. An existing data set was used to derive traffic light cut-offs for low (red), intermediate (amber), and higher (green) states of patient arousal. The validity of these was prospectively evaluated in 30 sedated critically ill patients against hourly Richmond Agitation Sedation Scale (RASS) assessments with concealment of RI data from clinical staff. RESULTS: With derivation data, an RI less than or equal to 35 had best discrimination for a Ramsay score of 5/6 (sensitivity, 90%; specificity, 79%). For traffic lights, we chose RI less than or equal to 20 as red, 20 to 40 as amber, and more than 40 as green. In the prospective study, RI values were red/amber for 76% of RASS -5/-4 assessments, but RI varied dynamically over time in many patients, and discordance with RASS may have resulted from the use of 1 hour of data for RI calculations. We also noted that red/amber values resulted from sleep, encephalopathy, and low levels of stimulation. CONCLUSIONS: Responsiveness Index is not directly comparable with clinical sedation scores but is a potential continuous alert to possible deep sedation in critically ill patients.