Andrew Coggins, Sun Song Hong, Kaushik Baliga, Louis P Halamek
{"title":"Immediate faculty feedback using debriefing timing data and conversational diagrams.","authors":"Andrew Coggins, Sun Song Hong, Kaushik Baliga, Louis P Halamek","doi":"10.1186/s41077-022-00203-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Debriefing is an essential skill for simulation educators and feedback for debriefers is recognised as important in progression to mastery. Existing assessment tools, such as the Debriefing Assessment for Simulation in Healthcare (DASH), may assist in rating performance but their utility is limited by subjectivity and complexity. Use of quantitative data measurements for feedback has been shown to improve performance of clinicians but has not been studied as a focus for debriefer feedback.</p><p><strong>Methods: </strong>A multi-centre sample of interdisciplinary debriefings was observed. Total debriefing time, length of individual contributions and demographics were recorded. DASH scores from simulation participants, debriefers and supervising faculty were collected after each event. Conversational diagrams were drawn in real-time by supervising faculty using an approach described by Dieckmann. For each debriefing, the data points listed above were compiled on a single page and then used as a focus for feedback to the debriefer.</p><p><strong>Results: </strong>Twelve debriefings were included (µ = 6.5 simulation participants per event). Debriefers receiving feedback from supervising faculty were physicians or nurses with a range of experience (n = 7). In 9/12 cases the ratio of debriefer to simulation participant contribution length was ≧ 1:1. The diagrams for these debriefings typically resembled a fan-shape. Debriefings (n = 3) with a ratio < 1:1 received higher DASH ratings compared with the ≧ 1:1 group (p = 0.038). These debriefings generated star-shaped diagrams. Debriefer self-rated DASH scores (µ = 5.08/7.0) were lower than simulation participant scores (µ = 6.50/7.0). The differences reached statistical significance for all 6 DASH elements. Debriefers evaluated the 'usefulness' of feedback and rated it 'highly' (µ= 4.6/5).</p><p><strong>Conclusion: </strong>Basic quantitative data measures collected during debriefings may represent a useful focus for immediate debriefer feedback in a healthcare simulation setting.</p>","PeriodicalId":72108,"journal":{"name":"Advances in simulation (London, England)","volume":"7 1","pages":"7"},"PeriodicalIF":2.8000,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8899451/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in simulation (London, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s41077-022-00203-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Debriefing is an essential skill for simulation educators and feedback for debriefers is recognised as important in progression to mastery. Existing assessment tools, such as the Debriefing Assessment for Simulation in Healthcare (DASH), may assist in rating performance but their utility is limited by subjectivity and complexity. Use of quantitative data measurements for feedback has been shown to improve performance of clinicians but has not been studied as a focus for debriefer feedback.
Methods: A multi-centre sample of interdisciplinary debriefings was observed. Total debriefing time, length of individual contributions and demographics were recorded. DASH scores from simulation participants, debriefers and supervising faculty were collected after each event. Conversational diagrams were drawn in real-time by supervising faculty using an approach described by Dieckmann. For each debriefing, the data points listed above were compiled on a single page and then used as a focus for feedback to the debriefer.
Results: Twelve debriefings were included (µ = 6.5 simulation participants per event). Debriefers receiving feedback from supervising faculty were physicians or nurses with a range of experience (n = 7). In 9/12 cases the ratio of debriefer to simulation participant contribution length was ≧ 1:1. The diagrams for these debriefings typically resembled a fan-shape. Debriefings (n = 3) with a ratio < 1:1 received higher DASH ratings compared with the ≧ 1:1 group (p = 0.038). These debriefings generated star-shaped diagrams. Debriefer self-rated DASH scores (µ = 5.08/7.0) were lower than simulation participant scores (µ = 6.50/7.0). The differences reached statistical significance for all 6 DASH elements. Debriefers evaluated the 'usefulness' of feedback and rated it 'highly' (µ= 4.6/5).
Conclusion: Basic quantitative data measures collected during debriefings may represent a useful focus for immediate debriefer feedback in a healthcare simulation setting.