Understanding nurses’ decision-making when managing weaning from mechanical ventilation: a study of novice and experienced critical care nurses in Scotland and Greece.

Aim and objectives To examine how nurses collect and use cues from respiratory assessment to inform their decisions as they wean patients from ventilatory support. Background Prompt and accurate identification of the patient's ability to sustain reduction of ventilatory support has the potential to increase the likelihood of successful weaning. Nurses' information processing during the weaning from mechanical ventilation has not been well-described. Design A descriptive ethnographic study exploring critical care nurses' decision-making processes when weaning mechanically ventilated patients from ventilatory support in the real setting. Methods Novice and expert Scottish and Greek nurses from two tertiary intensive care units were observed in real practice of weaning mechanical ventilation and were invited to participate in reflective interviews near the end of their shift. Data were analysed thematically using concept maps based on information processing theory. Ethics approval and informed consent were obtained. Results Scottish and Greek critical care nurses acquired patient-centred objective physiological and subjective information from respiratory assessment and previous knowledge of the patient, which they clustered around seven concepts descriptive of the patient's ability to wean. Less experienced nurses required more encounters of cues to attain the concepts with certainty. Subjective criteria were intuitively derived from previous knowledge of patients' responses to changes of ventilatory support. All nurses used focusing decision-making strategies to select and group cues in order to categorise information with certainty and reduce the mental strain of the decision task. Conclusions Nurses used patient-centred information to make a judgment about the patients' ability to wean. Decision-making strategies that involve categorisation of patient-centred information can be taught in bespoke educational programmes for mechanical ventilation and weaning. Relevance to clinical practice Advanced clinical reasoning skills and accurate detection of cues in respiratory assessment by critical care nurses will ensure optimum patient management in weaning mechanical ventilation

Evaluation of ventilation performance in public spaces.

Smoking restrictions in the workplace and increased health consciousness at home have seen a sizable reduction in the number of spaces where smoking is permissible. The aim of this study was to investigate the effects of ventilation in public houses, one of the few remaining public spaces where smoking is still socially acceptable. Little is known about the situation with shared occupancies, where relatively large areas are intended to accommodate both smokers and non-smokers. This study clearly identifies potential problems with a simplistic design approach to ventilation and its effectiveness in the context of shared occupancy spaces. A computational fluid dynamics code has been used to model airflows with the aim of identifying inefficiencies in existing ventilation systems.

Do simple ventilation and gas exchange measurements predict early successful weaning from respiratory support in unselected general intensive care patients?

Background. The value of respiratory variables as weaning predictors in the intensive care unit (ICU) is controversial. We evaluated the ability of tidal volume (Vtexp), respiratory rate ( f ), minute volume (MVexp), rapid shallow breathing index ( f/Vt), inspired–expired oxygen concentration difference [(I–E)O2], and end-tidal carbon dioxide concentration (PE′CO2) at the end of a weaning trial to predict early weaning outcomes. Methods. Seventy-three patients who required .24 h of mechanical ventilation were studied. A controlled pressure support weaning trial was undertaken until 5 cm H2O continuous positive airway pressure or predefined criteria were reached. The ability of data from the last 5 min of the trial to predict whether a predefined endpoint indicating discontinuation of ventilator support within the next 24 h was evaluated. Results. Pre-test probability for achieving the outcome was 44% in the cohort (n¼32). Non-achievers were older, had higher APACHE II and organ failure scores before the trial, and higher baseline arterial H+ concentrations. The Vt, MV, f, and f/Vt had no predictive power using a range of cut-off values or from receiver operating characteristic (ROC) analysis. The [I–E]O2 and PE′CO2 had weak discriminatory power [areaunder the ROC curve: [I–E]O2 0.64 (P¼0.03); PE′CO2 0.63 (P¼0.05)]. Using best cut-off values for [I–E]O2 of 5.6% and PE′CO2 of 5.1 kPa, positive and negative likelihood ratios were 2 and 0.5, respectively, which only changed the pre- to post-test probability by about 20%. Conclusions. In unselected ICU patients, respiratory variables predict early weaning from mechanical ventilation poorly.

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