Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study

Abstract 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 de...

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Main Authors: Ronaldo Sevilla-Berrios, John C. O’Horo, Christopher N. Schmickl, Aysen Erdogan, Xiaomei Chen, Lisbeth Y. Garcia Arguello, Yue Dong, Oguz Kilickaya, Brain Pickering, Rahul Kashyap, Ognjen Gajic
Format: Article
Language:English
Published: BMC 2018-04-01
Series:International Journal of Emergency Medicine
Online Access:http://link.springer.com/article/10.1186/s12245-018-0185-8
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author Ronaldo Sevilla-Berrios
John C. O’Horo
Christopher N. Schmickl
Aysen Erdogan
Xiaomei Chen
Lisbeth Y. Garcia Arguello
Yue Dong
Oguz Kilickaya
Brain Pickering
Rahul Kashyap
Ognjen Gajic
author_facet Ronaldo Sevilla-Berrios
John C. O’Horo
Christopher N. Schmickl
Aysen Erdogan
Xiaomei Chen
Lisbeth Y. Garcia Arguello
Yue Dong
Oguz Kilickaya
Brain Pickering
Rahul Kashyap
Ognjen Gajic
author_sort Ronaldo Sevilla-Berrios
collection DOAJ
description Abstract 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.
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spelling doaj.art-0e53ca63148e43e38bf7f5fe29cd3ec22022-12-22T00:39:45ZengBMCInternational Journal of Emergency Medicine1865-13721865-13802018-04-011111610.1186/s12245-018-0185-8Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation studyRonaldo Sevilla-Berrios0John C. O’Horo1Christopher N. Schmickl2Aysen Erdogan3Xiaomei Chen4Lisbeth Y. Garcia Arguello5Yue Dong6Oguz Kilickaya7Brain Pickering8Rahul Kashyap9Ognjen Gajic10Department of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicMETRIC, Mayo ClinicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicMETRIC, Mayo ClinicMETRIC, Mayo ClinicMETRIC, Mayo ClinicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Mayo ClinicAbstract 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.http://link.springer.com/article/10.1186/s12245-018-0185-8
spellingShingle Ronaldo Sevilla-Berrios
John C. O’Horo
Christopher N. Schmickl
Aysen Erdogan
Xiaomei Chen
Lisbeth Y. Garcia Arguello
Yue Dong
Oguz Kilickaya
Brain Pickering
Rahul Kashyap
Ognjen Gajic
Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study
International Journal of Emergency Medicine
title Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study
title_full Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study
title_fullStr Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study
title_full_unstemmed Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study
title_short Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study
title_sort prompting with electronic checklist improves clinician performance in medical emergencies a high fidelity simulation study
url http://link.springer.com/article/10.1186/s12245-018-0185-8
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