RESUMO
BACKGROUND: Inefficient processes of care delivery during acute resuscitation can compromise the "Golden Hour," the time when quick interventions can rapidly determine the course of the patient's outcome. Checklists have been shown to be an effective tool for standardizing care models. We developed a novel electronic tool, the Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN) to facilitate standardized evaluation and treatment approach for acutely decompensating patients. The checklist was enforced by the use of a "prompter," a team member separate from the leader who records and reviews pertinent CERTAIN algorithms and verbalizes these to the team. Our hypothesis was that the CERTAIN model, with the use of the tool and a prompter, can improve clinician performance and satisfaction in the evaluation of acute decompensating patients in a simulated environment. METHODS: Volunteer clinicians with valid adult cardiac life support (ACLS) certification were invited to test the CERTAIN model in a high-fidelity simulation center. The first session was used to establish a baseline evaluation in a standard clinical resuscitation scenario. Each subject then underwent online training before returning to a simulation center for a live didactic lecture, software knowledge assessment, and practice scenarios. Each subject was then evaluated on a scenario with a similar content to the baseline. All subjects took a post-experience satisfaction survey. Video recordings of the pre-and post-test sessions were evaluated using a validated method by two blinded reviewers. RESULTS: Eighteen clinicians completed baseline and post-education sessions. CERTAIN prompting was associated with reduced omissions of critical tasks (46 to 32%, p < 0.01) and 12 out of 14 general assessment tasks were completed in a more timely manner. The post-test survey indicated that 72% subjects felt better prepared during an emergency scenario using the CERTAIN model and 85% would want to be treated with the CERTAIN if they were critically ill. CONCLUSION: Prompting with electronic checklist improves clinicians' performance and satisfaction when dealing with medical emergencies in high-fidelity simulation environment.
RESUMO
BACKGROUND: Critical illness is a time-sensitive process which requires practitioners to process vast quantities of data and make decisions rapidly. We have developed a tool, the Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN), aimed at enhancing care delivery in such situations. To determine the efficacy of CERTAIN and similar cognitive aids, we developed rubric for evaluating provider performance in a simulated medical resuscitation environments. METHODS: We recruited 18 clinicians with current valid ACLS certification for evaluation in three simulated medical scenarios designed to mimic typical medical decompensation events routinely experienced in clinical care. Subjects were stratified as experienced or novice based on prior critical care training. A checklist of critical actions was designed using face validity for each scenario to evaluate task completion and performance. Simulation sessions were video recorded and scored by two independent raters. Construct validity was assessed under the assumption that experienced clinicians should perform better than novice clinicians on each task. Reliability was assessed as percentage agreement, kappa statistics and Bland-Altman plots as appropriate. RESULTS: Eleven experts and seven novices completed evaluation. The overall agreement on common checklist item completion was 84.8 %. The overall model achieved face validity and was consistent with our construct, with experienced clinicians trending towards better performance compared to novices for accuracy and speed of task completion. CONCLUSIONS: A standardized video assessment tool has potential to provide a valid and reliable method to assess 12 performances of clinicians facing simulated medical emergencies.
