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

Ronaldo Sevilla-Berrios, John C. O’Horo, Christopher N. Schmickl, Aysen Erdogan, Xiaomei Chen, Lisbeth Y. Garcia Arguello, Yue Dong, Oguz Kilickaya, Brian W Pickering, Rahul Kashyap, Ognjen Gajic

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish (US)
Article number26
JournalInternational Journal of Emergency Medicine
Volume11
Issue number1
DOIs
StatePublished - Dec 1 2018

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Checklist
Emergencies
Resuscitation
Therapeutics
Video Recording
Certification
Critical Illness
Volunteers
Software
Education

ASJC Scopus subject areas

  • Emergency Medicine

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Prompting with electronic checklist improves clinician performance in medical emergencies : a high-fidelity simulation study. / Sevilla-Berrios, Ronaldo; O’Horo, John C.; Schmickl, Christopher N.; Erdogan, Aysen; Chen, Xiaomei; Garcia Arguello, Lisbeth Y.; Dong, Yue; Kilickaya, Oguz; Pickering, Brian W; Kashyap, Rahul; Gajic, Ognjen.

In: International Journal of Emergency Medicine, Vol. 11, No. 1, 26, 01.12.2018.

Research output: Contribution to journalArticle

Sevilla-Berrios, R, O’Horo, JC, Schmickl, CN, Erdogan, A, Chen, X, Garcia Arguello, LY, Dong, Y, Kilickaya, O, Pickering, BW, Kashyap, R & Gajic, O 2018, 'Prompting with electronic checklist improves clinician performance in medical emergencies: a high-fidelity simulation study', International Journal of Emergency Medicine, vol. 11, no. 1, 26. https://doi.org/10.1186/s12245-018-0185-8
Sevilla-Berrios, Ronaldo ; O’Horo, John C. ; Schmickl, Christopher N. ; Erdogan, Aysen ; Chen, Xiaomei ; Garcia Arguello, Lisbeth Y. ; Dong, Yue ; Kilickaya, Oguz ; Pickering, Brian W ; Kashyap, Rahul ; Gajic, Ognjen. / Prompting with electronic checklist improves clinician performance in medical emergencies : a high-fidelity simulation study. In: International Journal of Emergency Medicine. 2018 ; Vol. 11, No. 1.
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AU - Erdogan, Aysen

AU - Chen, Xiaomei

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