Faster clinical response to the onset of adverse events: A wearable metacognitive attention aid for nurse triage of clinical alarms.

OBJECTIVE: This study evaluates the potential for improving patient safety by introducing a metacognitive attention aid that enables clinicians to more easily access and use existing alarm/alert information. It is hypothesized that this introduction will enable clinicians to easily triage alarm/alert events and quickly recognize emergent opportunities to adapt care delivery. The resulting faster response to clinically important alarms/alerts has the potential to prevent adverse events and reduce healthcare costs. MATERIALS AND METHODS: A randomized within-subjects single-factor clinical experiment was conducted in a high-fidelity 20-bed simulated acute care hospital unit. Sixteen registered nurses, four at a time, cared for five simulated patients each. A two-part highly realistic clinical scenario was used that included representative: tasking; information; and alarms/alerts. The treatment condition introduced an integrated wearable attention aid that leveraged metacognition methods from proven military systems. The primary metric was time for nurses to respond to important alarms/alerts. RESULTS: Use of the wearable attention aid resulted in a median relative within-subject improvement for individual nurses of 118% (W = 183, p = 0.006). The top quarter of relative improvement was 3,303% faster (mean; 17.76 minutes reduced to 1.33). For all unit sessions, there was an overall 148% median faster response time to important alarms (8.12 minutes reduced to 3.27; U = 2.401, p = 0.016), with 153% median improvement in consistency across nurses (F = 11.670, p = 0.001). DISCUSSION AND CONCLUSION: Existing device-centric alarm/alert notification solutions can require too much time and effort for nurses to access and understand. As a result, nurses may ignore alarms/alerts as they focus on other important work. There has been extensive research on reducing alarm frequency in healthcare. However, alarm safety remains a top problem. Empirical observations reported here highlight the potential of improving patient safety by supporting the meta-work of checking alarms.

Graphical arterial blood gas visualization tool supports rapid and accurate data interpretation.

A visualization tool that integrates numeric information from an arterial blood gas report with novel graphics was designed for the purpose of promoting rapid and accurate interpretation of acid-base data. A study compared data interpretation performance when arterial blood gas results were presented in a traditional numerical list versus the graphical visualization tool. Critical-care nurses (n = 15) and nursing students (n = 15) were significantly more accurate identifying acid-base states and assessing trends in acid-base data when using the graphical visualization tool. Critical-care nurses and nursing students using traditional numerical data had an average accuracy of 69% and 74%, respectively. Using the visualization tool, average accuracy improved to 83% for critical-care nurses and 93% for nursing students. Analysis of response times demonstrated that the visualization tool might help nurses overcome the "speed/accuracy trade-off" during high-stress situations when rapid decisions must be rendered. Perceived mental workload was significantly reduced for nursing students when they used the graphical visualization tool. In this study, the effects of implementing the graphical visualization were greater for nursing students than for critical-care nurses, which may indicate that the experienced nurses needed more training and use of the new technology prior to testing to show similar gains. Results of the objective and subjective evaluations support the integration of this graphical visualization tool into clinical environments that require accurate and timely interpretation of arterial blood gas data.

Graphical arterial blood gas visualization tool supports rapid and accurate data interpretation.

A visualization tool that integrates numeric information from an arterial blood gas report with novel graphics was designed for the purpose of promoting rapid and accurate interpretation of acid-base data. A study compared data interpretation performance when arterial blood gas results were presented in a traditional numerical list versus the graphical visualization tool. Critical-care nurses (n = 15) and nursing students (n = 15) were significantly more accurate identifying acid-base states and assessing trends in acid-base data when using the graphical visualization tool. Critical-care nurses and nursing students using traditional numerical data had an average accuracy of 69% and 74%, respectively. Using the visualization tool, average accuracy improved to 83% for critical-care nurses and 93% for nursing students. Analysis of response times demonstrated that the visualization tool might help nurses overcome the "speed/accuracy trade-off" during high-stress situations when rapid decisions must be rendered. Perceived mental workload was significantly reduced for nursing students when they used the graphical visualization tool. In this study, the effects of implementing the graphical visualization were greater for nursing students than for critical-care nurses, which may indicate that the experienced nurses needed more training and use of the new technology prior to testing to show similar gains. Results of the objective and subjective evaluations support the integration of this graphical visualization tool into clinical environments that require accurate and timely interpretation of arterial blood gas data.

Response surface model predictions of emergence and response to pain in the recovery room: An evaluation of patients emerging from an isoflurane and fentanyl anesthetic.

INTRODUCTION: Sevoflurane-remifentanil interaction models that predict responsiveness and response to painful stimuli have been evaluated in patients undergoing elective surgery. Preliminary evaluations of model predictions were found to be consistent with observations in patients anesthetized with sevoflurane, remifentanil, and fentanyl. This study explored the feasibility of adapting the predictions of sevoflurane-remifentanil interaction models to an isoflurane-fentanyl anesthetic. We hypothesized that model predictions adapted for isoflurane and fentanyl are consistent with observed patient responses and are similar to the predictions observed in our previous work with sevoflurane-remifentanil/fentanyl anesthetics. METHODS: Twenty-five patients scheduled for elective surgery received a fentanyl-isoflurane anesthetic. Model predictions of unresponsiveness were recorded at emergence, and predictions of a response to noxious stimulus were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. Results were also compared with our previous predictions after the administration of a sevoflurane-remifentanil/fentanyl anesthetic. RESULTS: Although patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). After the termination of the anesthetic, model predictions of responsiveness well described the actual fraction of patients observed to be responsive during emergence. Half of the patients woke within 2 min of the 50% model-predicted probability of unresponsiveness; 70% woke within 4 min. Similarly, predictions of a response to a noxious stimulus were consistent with the number of patients who required fentanyl in the recovery room. Model predictions after the administration of an isoflurane-fentanyl anesthetic were similar to model predictions after a sevoflurane-remifentanil/fentanyl anesthetic. DISCUSSION: The results confirmed our study hypothesis; model predictions for unresponsiveness and no response to painful stimuli, adapted to isoflurane-fentanyl were consistent with observations. These results were similar to our previous study comparing model predictions and patient observations after a sevoflurane-remifentanil/fentanyl anesthetic.

An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations.

INTRODUCTION: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions. METHODS: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. RESULTS: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models. DISCUSSION: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.

Part Task and variable priority training in first-year anesthesia resident education: a combined didactic and simulation-based approach to improve management of adverse airway and respiratory events.

BACKGROUND: Part task training (PTT) focuses on dividing complex tasks into components followed by intensive concentrated training on individual components. Variable priority training (VPT) focuses on optimal distribution of attention when performing multiple tasks simultaneously with the goal of flexible allocation of attention. This study explored how principles of PTT and VPT adapted to anesthesia training would improve first-year anesthesiology residents' management of simulated adverse airway and respiratory events. The authors hypothesized that participants with PTT and VPT would perform better than those with standard training. METHODS: Twenty-two first-year anesthesia residents were randomly divided into two groups and trained over 12 months. The control group received standard didactic and simulation-based training. The experimental group received similar training but with emphasis on PTT and VPT techniques. Participant ability to manage seven adverse airway and respiratory events were assessed before and after the training period. Performance was measured by the number of correct tasks, making a correct diagnosis, assessment of perceived workload, and an assessment of scenario comprehension. RESULTS: Participants in both groups exhibited significant improvement in all metrics after a year of training. Participants in the experimental group were able to complete more tasks and answered more comprehension questions correctly. There was no difference in perceived workload or the number of correct diagnoses between groups. CONCLUSION: This study in part confirmed the study hypotheses. The results suggest that VPT and PTT are promising adjuncts to didactic and simulation-based training for management of adverse airway and respiratory events.

An evaluation of remifentanil propofol response surfaces for loss of responsiveness, loss of response to surrogates of painful stimuli and laryngoscopy in patients undergoing elective surgery.

INTRODUCTION: In this study, we explored how a set of remifentanil-propofol response surface interaction models developed from data collected in volunteers would predict responses to events in patients undergoing elective surgery. Our hypotheses were that these models would predict a patient population's loss and return of responsiveness and the presence or absence of a response to laryngoscopy and the response to pain after surgery. METHODS: Twenty-one patients were enrolled. Anesthesia consisted of remifentanil and propofol infusions and fentanyl boluses. Loss and return of responsiveness, responses to laryngoscopy, and responses to postoperative pain were assessed in each patient. Model predictions were compared with observed responses. RESULTS: The loss of responsiveness model predicted that patients would become unresponsive 2.4 +/- 2.6 min earlier than observed. At the time of laryngoscopy, the laryngoscopy model predicted an 89% probability of no response to laryngoscopy and 81% did not respond. During emergence, the loss of responsiveness model predicted return of responsiveness 0.6 +/- 5.1 min before responsiveness was observed. The mean probability of no response to pressure algometry was 23% +/- 35% when patients required fentanyl for pain control. DISCUSSION: This preliminary assessment of a series of remifentanil-propofol interaction models demonstrated that these models predicted responses to selected pertinent events during elective surgery. However, significant model error was evident during rapid changes in predicted effect-site propofol-remifentanil concentration pairs.

A simulation-based evaluation of a graphic cardiovascular display.

INTRODUCTION: A graphic presentation of complex information can facilitate early detection and management of adverse events. Prior work found that graphical presentation of selected cardiovascular variables led to earlier detection of a simulated ischemic event. Based on these findings, a second evaluation explored the utility of a graphical cardiovascular display (GCD) in a variety of simulated adverse cardiopulmonary events for two different display configurations. In this evaluation, we revised the GCD to present hemodynamic variables with or without a pulmonary artery catheter. Our hypotheses were that the revised GCD would improve detection of adverse cardiopulmonary events and add no additional perceived workload. METHODS: Sixteen anesthesiologists and anesthesia residents were enrolled in a simulation-based evaluation of the GCD. Participants were randomly split into two groups balanced for expertise and asked to manage six simulated adverse cardiopulmonary events. The GCD was present in half of the simulations, balanced across scenarios and groups. Participants' verbalizations and actions during each scenario were recorded and transcribed. Transcripts of treatment interventions were subsequently rated by two blinded expert anesthesiologists. Perceived workload, time to detection, and proper treatment of the adverse event were compared between groups. RESULTS: Experts ranked anesthesiologists using the GCD as being more effective overall and individually in three of six scenarios. Use of the GCD was demonstrated to influence the time to detection and the time to treatment of some critical events. There were no workload differences between display groups. DISCUSSION: Treatment intervention by participants using the GCD was rated superior by two blinded experts. The presence of the GCD resulted in a modest improvement in the time to detect myocardial ischemia and increased pulmonary capillary wedge pressure. The GCD may be a useful adjunct to monitor patients during adverse cardiopulmonary events.

Development and evaluation of a graphical anesthesia drug display.

BACKGROUND: Usable real-time displays of intravenous anesthetic concentrations and effects could significantly enhance intraoperative clinical decision-making. Pharmacokinetic models are available to estimate past, present, and future drug effect-site concentrations, and pharmacodynamic models are available to predict the drug's associated physiologic effects. METHODS: An interdisciplinary research team (bioengineering, architecture, anesthesiology, computer engineering, and cognitive psychology) developed a graphic display that presents the real-time effect-site concentrations, normalized to the drugs' EC(95), of intravenous drugs. Graphical metaphors were created to show the drugs' pharmacodynamics. To evaluate the effect of the display on the management of total intravenous anesthesia, 15 anesthesiologists participated in a computer-based simulation study. The participants cared for patients during two experimental conditions: with and without the drug display. RESULTS: With the drug display, clinicians administered more bolus doses of remifentanil during anesthesia maintenance. There was a significantly lower variation in the predicted effect-site concentrations for remifentanil and propofol, and effect-site concentrations were maintained closer to the drugs' EC(95). There was no significant difference in the simulated patient heart rate and blood pressure with respect to experimental condition. The perceived performance for the participants was increased with the drug display, whereas mental demand, effort, and frustration level were reduced. In a post-simulation questionnaire, participants rated the display to be a useful addition to anesthesia monitoring. CONCLUSIONS: The drug display altered simulated clinical practice. These results, which will inform the next iteration of designs and evaluations, suggest promise for this approach to drug data visualization.