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Record W3082502956 · doi:10.1097/pec.0000000000002218

Innovating Pediatric Emergency Care and Learning Through Interprofessional Briefing and Workplace-Based Assessment

2020· article· en· W3082502956 on OpenAlexaff
Isabelle Steiner, Audrey Balsiger, Mark Goldszmidt, Sören Huwendiek

Bibliographic record

VenuePediatric Emergency Care · 2020
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern University
FundersUniversity of Bern
KeywordsMedicineIntensive careMedical emergencyNursingMedical educationIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Managing pediatric emergencies can be both clinically and educationally challenging with little existing research on how to improve resident involvement. Moreover, nursing input is frequently ignored. We report here on an innovation using interprofessional briefing (iB) and workplace-based assessment (iWBA) to improve the delivery of care, the involvement of residents, and their assessment. METHODS: Over a period of 3 months, we implement an innovation using iB and iWBA for residents providing emergency pediatric care. A constructivist thematic analysis approach was used to collect and analyze data from 4 focus groups (N = 18) with nurses (4), supervisors (5), and 2 groups of residents (4 + 5). RESULTS: Residents, supervisors, and nurses all felt that iB had positive impacts on learning, teamwork, and patient care. Moreover, when used, iB seemed to play an important role in enhancing the impact of iWBA. Although iB and iWBA seemed to be accepted and participants described important impacts on emergency department culture, conducting of both iB and iWBA could be sometimes challenging as opposed to iB alone mainly because of time constraints. CONCLUSIONS: Interprofessional briefing and iWBA are promising approaches for not only resident involvement and learning during pediatric emergencies but also enhancing team function and patient care. Nursing involvement was pivotal in the success of the innovation enhancing both care and resident learning.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.029
GPT teacher head0.408
Teacher spread0.379 · 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 designObservational
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

Citations5
Published2020
Admission routes1
Has abstractyes

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