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Record W4294219073 · doi:10.1186/s12873-022-00707-4

Implementation and facilitation of post-resuscitation debriefing: a comparative crossover study of two post-resuscitation debriefing frameworks

2022· article· en· W4294219073 on OpenAlexaff
April Kam, Clarelle L. Gonsalves, Samantha V. Nordlund, Stephen J. Hale, Jennifer Twiss, Cynthia Cupido, Mandeep Brar, Melissa Parker

Bibliographic record

VenueBMC Emergency Medicine · 2022
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsUniversity of ManitobaHospital for Sick ChildrenMcMaster UniversityMcMaster Children's Hospital
Fundersnot available
KeywordsDebriefingMedicineThematic analysisInterpersonal communicationResuscitationNursingQualitative researchMedical educationPsychologyEmergency medicineSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Post-resuscitation debriefing (PRD) is the process of facilitated, reflective discussion, enabling team-based interpersonal feedback and identification of systems-level barriers to patient care. The importance and benefits of PRD are well recognized; however, numerous barriers exist, preventing its practical implementation. Use of a debriefing tool can aid with facilitating debriefing, creating realistic objectives, and providing feedback. OBJECTIVES: To assess utility of two PRD tools, Debriefing In Situ Conversation after Emergent Resuscitation Now (DISCERN) and Post-Code Pause (PCP), through user preference. Secondary aims included evaluating differences in quality, subject matter, and types of feedback between tools and implications on quality improvement and patient safety. METHODS: Prospective, crossover study over a 12-month period from February 2019 to January 2020. Two PDR tools were implemented in 8 week-long blocks in acute care settings at a tertiary care children's hospital. Debriefings were triggered for any intubation, resuscitation, serious/unanticipated patient outcome, or by request for distressing situations. Post-debriefing, team members completed survey evaluations of the PDR tool used. Descriptive statistics were used to analyze survey responses. A thematic analysis was conducted to identify themes that emerged from qualitative responses. RESULTS: A total of 114 debriefings took place, representing 655 total survey responses, 327 (49.9%) using PCP and 328 (50.1%) using DISCERN. 65.2% of participants found that PCP provided emotional support while only 50% of respondents reported emotional support from DISCERN. PCP was found to more strongly support clinical education (61.2% vs 56.7%). There were no significant differences in ease of use, support of the debrief process, number of newly identified improvement opportunities, or comfort in making comments or raising questions during debriefs between tools. Thematic analysis revealed six key themes: communication, quality of care, team function & dynamics, resource allocation, preparation and response, and support. CONCLUSION: Both tools provide teams with an opportunity to reflect on critical events. PCP provided a more organized approach to debriefing, guided the conversation to key areas, and discussed team member wellbeing. When implementing a PRD tool, environmental constraints, desired level of emotional support, and the extent to which open ended data is deemed valuable should be considered.

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.

How this classification was reachedexpand

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.163
GPT teacher head0.481
Teacher spread0.318 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2022
Admission routes1
Has abstractyes

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