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Record W3011699699 · doi:10.1002/aet2.10444

Applications of Postresuscitation Debriefing Frameworks in Emergency Settings: A Systematic Review

2020· review· en· W3011699699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAEM Education and Training · 2020
Typereview
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDebriefingBest practiceQuality (philosophy)Medical educationPsychologyMedicineMEDLINEProcess managementMedical emergencyKnowledge managementNursingComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: Postresuscitation debriefing (PRD) is a valuable educational tool in emergency medicine. It is recommended by international resuscitation guidelines, has been shown to improve both patient outcomes and resuscitation team performance, and is frequently requested by medical learners. However, there is limited research comparing standardized debriefing frameworks. Not only does this hinder the ability of interested emergency departments (EDs) to adopt PRD, but it limits the quality of future debriefing research. We sought to identify and compare existing PRD frameworks to inform the implementation of effective PRD in emergency medicine. METHODS: We conducted a systematic review following PRISMA standards to identify debriefing frameworks used in the ED and other acute care settings for further analysis. Identified frameworks were analyzed and compared based on a method previously described in the literature. RESULTS: Our search identified six frameworks, which ranged from simple tools for immediate feedback to complex, hospital-wide systems engineering-based approaches to quality improvement. Key findings were the importance of ensuring debriefing facilitators are properly selected and trained and of tailoring framework design to specific organizational targets. However, there is limited validation data for these frameworks, and more study is needed to identify and validate true best practices in PRD. CONCLUSIONS: All six identified frameworks seem to be effective methods of debriefing. Given the breadth in debriefing methods and goals identified, this suggests that there may not be a one-size-fits-all approach to PRD and that organizations should instead identify their own unique needs and barriers and adopt the debriefing framework that best addresses those needs. Other findings were the importance of well-trained debriefing facilitators and the use of clear roles in organizing debriefings. Further research is needed to assess the effectiveness of postresuscitation frameworks with regard to both team performance and patient outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.431
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it