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Senter-Zapata M, Neel DV, Colocci I, Alblooshi A, AlRadini FAM, Quach B, Lyon S, Coll M, Chu A, Rainer KW, Waters B, Baugh CW, Dias RD, Zhang H, Eyre A, Isselbacher E, Conley J, Carlile N. An Advanced Cardiac Life Support Application Improves Performance during Simulated Cardiac Arrest. Appl Clin Inform 2024; 15:798-807. [PMID: 39357878 PMCID: PMC11446628 DOI: 10.1055/s-0044-1788979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 07/18/2024] [Indexed: 10/04/2024] Open
Abstract
OBJECTIVES Variability in cardiopulmonary arrest training and management leads to inconsistent outcomes during in-hospital cardiac arrest. Existing clinical decision aids, such as American Heart Association (AHA) advanced cardiovascular life support (ACLS) pocket cards and third-party mobile apps, often lack comprehensive management guidance. We developed a novel, guided ACLS mobile app and evaluated user performance during simulated cardiac arrest according to the 2020 AHA ACLS guidelines via randomized controlled trial. METHODS Forty-six resident physicians were randomized to lead a simulated code team using the AHA pockets cards (N = 22) or the guided app (N = 24). The primary outcome was successful return of spontaneous circulation (ROSC). Secondary outcomes included code leader stress and confidence, AHA ACLS guideline adherence, and errors. A focus group of 22 residents provided feedback. Statistical analysis included two-sided t-tests and Fisher's exact tests. RESULTS App users showed significantly higher ROSC rate (50 vs. 18%; p = 0.024), correct thrombolytic administration (54 vs. 23%; p = 0.029), backboard use (96 vs. 27%; p < 0.001), end-tidal CO2 monitoring (58 vs. 27%; p = 0.033), and confidence compared with baseline (1.0 vs 0.3; p = 0.005) compared with controls. A focus group of 22 residents indicated unanimous willingness to use the app, with 82% preferring it over AHA pocket cards. CONCLUSION Our guided ACLS app shows potential to improve user confidence and adherence to the AHA ACLS guidelines and may help to standardize in-hospital cardiac arrest management. Further validation studies are essential to confirm its efficacy in clinical practice.
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Affiliation(s)
- Michael Senter-Zapata
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
- Healthcare Transformation Lab, Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Dylan V. Neel
- Harvard Medical School, Boston, Massachusetts, United States
| | | | - Afaf Alblooshi
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Department of Medical Education, United Arab Emirates University College of Medicine and Health Sciences, Al Ain, Abu Dhabi, United Arab Emirates
| | - Faten Abdullah M. AlRadini
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Department of Clinical Sciences, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Brian Quach
- Brigham and Women's Hospital, Boston, Massachusetts, United States
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, United States
| | - Samuel Lyon
- Harvard Medical School, Boston, Massachusetts, United States
| | - Maxwell Coll
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
| | - Andrew Chu
- Healthcare Transformation Lab, Massachusetts General Hospital, Boston, Massachusetts, United States
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | | | - Beth Waters
- Brigham and Women's Faulkner Hospital, Jamaica Plain, Massachusetts, United States
| | - Christopher W. Baugh
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
| | - Roger D. Dias
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, United States
| | - Haipeng Zhang
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
- Brigham Digital Innovation Hub, Brigham and Women's Hospital, Hale Building for Transformative Medicine, Boston, Massachusetts, United States
| | - Andrew Eyre
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, United States
| | - Eric Isselbacher
- Harvard Medical School, Boston, Massachusetts, United States
- Healthcare Transformation Lab, Massachusetts General Hospital, Boston, Massachusetts, United States
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Jared Conley
- Harvard Medical School, Boston, Massachusetts, United States
- Healthcare Transformation Lab, Massachusetts General Hospital, Boston, Massachusetts, United States
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Narath Carlile
- Harvard Medical School, Boston, Massachusetts, United States
- Brigham and Women's Hospital, Boston, Massachusetts, United States
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