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Stefanidis D, Cook D, Kalantar-Motamedi SM, Muret-Wagstaff S, Calhoun AW, Lauridsen KG, Paige JT, Lockey A, Donoghue A, Hall AK, Patocka C, Palaganas J, Gross IT, Kessler D, Vermylen J, Lin Y, Aebersold M, Chang TP, Duff J, Kolbe M, Rutherford-Hemming T, Decker S, Collings A, Toseef Ansari M. Society for Simulation in Healthcare Guidelines for Simulation Training. Simul Healthc 2024; 19:S4-S22. [PMID: 38240614 DOI: 10.1097/sih.0000000000000776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
BACKGROUND Simulation has become a staple in the training of healthcare professionals with accumulating evidence on its effectiveness. However, guidelines for optimal methods of simulation training do not currently exist. METHODS Systematic reviews of the literature on 16 identified key questions were conducted and expert panel consensus recommendations determined using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology. OBJECTIVE These evidence-based guidelines from the Society for Simulation in Healthcare intend to support healthcare professionals in decisions on the most effective methods for simulation training in healthcare. RESULTS Twenty recommendations on 16 questions were determined using GRADE. Four expert recommendations were also provided. CONCLUSIONS The first evidence-based guidelines for simulation training are provided to guide instructors and learners on the most effective use of simulation in healthcare.
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Affiliation(s)
- Dimitrios Stefanidis
- From the Department of Surgery (D.S., S.-M.K.-M.), Indiana University School of Medicine, Indianapolis, IN; Department of Internal Medicine (D.C.), Mayo Clinic, Rochester, MN; Department of Surgery (S.M.-W.), Emory University, Atlanta, GA; Department of Pediatrics (A.W.C.), University of Louisville School of Medicine and Norton Children's Medical Group, Louisville, KY; Department of Medicine (K.G.L.), Randers Regional Hospital, Randers, Denmark; Research Center for Emergency Medicine (K.G.L.), Aarhus University, Aarhus, Denmark; Department of Surgery (J.T.P.), LSU Health New Orleans School of Medicine, New Orleans, LA; Emergency Department (A.L.), Calderdale and Huddersfield NHS Trust, Halifax; School of Human and Health Sciences (A.L.), University of Huddersfield, Huddersfield, UK; Critical Care Medicine and Pediatrics (A.D.), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA; Department of Emergency Medicine (A.K.H.), University of Ottawa, Ottawa, Ontario, Canada; Department of Emergency Medicine (C.P.), Cumming School of Medicine University of Calgary, Calgary, AB, Canada; Department of Health Professions Education (J.P.), School of Healthcare Leadership, MGH Institute of Health Professions, Boston, MA; Department of Pediatrics (I.T.G.), Section of Emergency Medicine, Yale University, New Haven, CT; Department of Emergency Medicine (D.K.), Columbia University Vagelos College of Physicians and Surgeons, New York, NY,; Department of Medicine and Medical Education (J.V.), Feinberg School of Medicine, Northwestern University, Chicago, IL; KidSIM Simulation Research Program (Y.L.), Alberta Children's Hospital, Calgary, Canada; University of Michigan School of Nursing (M.A.), Ann Arbor, MI; Las Madrinas Simulation Center, Children's Hospital (T.C.), University South California, Los Angeles, CA; Department of Pediatrics (J.D.), University of Alberta, Edmonton, Alberta, Canada; Simulation Center (M.K.), University Hospital Zurich, ETH Zurich, Switzerland; Department of Nursing (T.R.-H.), University of North Carolina, Chapel Hill, NC; Department of Nursing (S.D.), Texas Tech University Health Sciences Center, Lubbock, TX; Department of Surgery (A.C.), University of Louisville, Louisville, KY; and Independent Methodologist (M.T.A.), Ottawa, Ontario, Canada
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Calhoun AW, Cook DA, Genova G, Motamedi SMK, Waseem M, Carey R, Hanson A, Chan JCK, Camacho C, Harwayne-Gidansky I, Walsh B, White M, Geis G, Monachino AM, Maa T, Posner G, Li DL, Lin Y. Educational and Patient Care Impacts of In Situ Simulation in Healthcare: A Systematic Review. Simul Healthc 2024; 19:S23-S31. [PMID: 38240615 DOI: 10.1097/sih.0000000000000773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
ABSTRACT This systematic review was performed to assess the effectiveness of in situ simulation education. We searched databases including MEDLINE and Embase for studies comparing in situ simulation with other educational approaches. Two reviewers screened articles and extracted information. Sixty-two articles met inclusion criteria, of which 24 were synthesized quantitatively using random effects meta-analysis. When compared with current educational practices alone, the addition of in situ simulation to these practices was associated with small improvements in clinical outcomes, including mortality [odds ratio, 0.66; 95% confidence interval (CI), 0.55 to 0.78], care metrics (standardized mean difference, -0.34; 95% CI, -0.45 to -0.21), and nontechnical skills (standardized mean difference, -0.52; 95% CI, -0.99 to -0.05). Comparisons between in situ and traditional simulation showed mixed learner preference and knowledge improvement between groups, while technical skills showed improvement attributable to in situ simulation. In summary, available evidence suggests that adding in situ simulation to current educational practices may improve patient mortality and morbidity.
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Affiliation(s)
- Aaron W Calhoun
- From the University of Louisville (A.C., G.G., A.H.), Louisville, KY; Mayo Multidisciplinary Simulation Center (D.A.C.), Mayo Clinic College of Medicine and Science, Rochester, MN; Indiana University School of Medicine (S.M.K.M.), Indianapolis, IN; Lincoln Medical Center (M.W.), Bronx New York, NY; University of Saskatchewan (R.C.), Saskatoon, Canada; The Chinese University of Hong Kong (J.C.K.C.), Hong Kong SAR; Center for Clinical Excellence (C.C., T.M.), Nationwide Children's Hospital, Ohio State University College of Medicine, Columbus, OH; Pediatric Critical Care Medicine (I.H.-G.), Bernard and Millie Duker Children's Hospital, Albany, NY; Boston University Chobanian & Avedisian School of Medicine (B.W.), Boston, MA; University of Alabama at Birmingham (M.W.), Birmingham, AL; Cincinnati Children's Hospital (G.G.), Cincinnati, OH; Center for Simulation, Advanced Education, and Innovation (A.M.M.), Children's Hospital of Philadelphia, Philadelphia, PA; University of Ottawa Skills & Simulation Centre (G.P.), University of Ottawa, Ontario, Canada; Department of Critical Care (D.L.L.), Zhongnan Hospital of Wuhan University, Wuhan, China; and University of Calgary (Y.L.), Calgary, Canada
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Suharsono T, Sunarmi S, Ida N, Khirria BN, Asrin N, Ulya I. The implementation of code blue by nurses as first responders in outpatient and inpatient rooms at Malang Indonesia Hospital. HEALTHCARE IN LOW-RESOURCE SETTINGS 2023. [DOI: 10.4081/hls.2023.11217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023] Open
Abstract
Introduction: In-Hospital Cardiac Arrest (IHCA) is a frequent occurrence that necessitates prompt and appropriate assistance to improve survival rates. Nurses in public care rooms and outpatients are expected to be first responders to IHCA until an activated hospital code blue team arrives. Therefore, this study aims to analyze the implementation of code blue response by nurses in outpatient and hospital inpatient rooms in Malang.
Design and Methods: This is a quantitative study that uses observational methods with a cross-sectional approach comprising of 109 inpatient and outpatient care room nurses from 9 hospitals in Malang. The implementation of code blue was measured by a simulated case of adult cardiac arrest in a hospital inpatient room.
Results: The nurses involved were 67.0% female, where the majority have a D3 education qualification (57.7%), with more than ten years working experience (45%). Furthermore, 83.5% of nurses work in regular care rooms and 16.5% come from outpatient rooms. The results showed that the implementation of code blue by nurses in regular care and inpatient rooms was 66.7% and 65.9%, respectively in the insufficient categories. In addition, the Mann-Whitney U test obtained a p-value of 0.929.
Conclusions: In conclusion, there was no significant difference in the implementation of code blue that occurred in the inpatient and outpatient rooms. Further studies were recommended to observe code blue events directly and take samples with balanced proportions.
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Implementation of a standardized robotic assistant surgical training curriculum. J Robot Surg 2021; 16:789-797. [PMID: 34435279 PMCID: PMC8387210 DOI: 10.1007/s11701-021-01291-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 07/31/2021] [Indexed: 11/02/2022]
Abstract
Since 2000, robotic-assisted surgery has rapidly expanded into almost every surgical sub-specialty. Despite the popularity of robotic surgery across the United States, a national consensus for standardized training and education of robotic surgeons or surgical teams remains absent. In this quality improvement initiative, a novel, stepwise iterative Robotic Assistant Surgical Training (RAST) curriculum was developed to broaden and standardize robotic bedside assistant training. Thirteen voluntary participants, capable of fulfilling the bedside assistant role, were evaluated to determine if RAST enhanced the learner's self-perceived level of confidence and comfort in their role as bedside assistant. A pre- and post-RAST training survey and a between-stages repeated-measures survey were conducted. All learner participants reported statistically significant increases in confidence and comfort after RAST training, (p = < 0.001), and between each stage, F (2, 24 = 60.47, p < .001; [Formula: see text] = 0.834). Participant feedback regarding curriculum improvement was obtained, suggesting the desire for more training and practice, in smaller groups of 2-3 participants. One hundred percent of participants felt RAST was beneficial and that it should be implemented as standardized training during onboarding for all robotic bedside assistants. Thus, a standardized, stepwise iterative robotic bedside assistant curriculum increases learner preparedness, comfort, and confidence, safely away from the patient bedside.
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