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Record W2899942607 · doi:10.1097/sih.0000000000000336

The Use of Statistical Process Control Charts to Evaluate Interprofessional Education Sessions Embedded Into a Pediatric Emergency In situ Resuscitation Program

2018· review· en· W2899942607 on OpenAlexaff
Jonathan Pirie, Sandra Cárdenas, Wail Seleem, Dragan Kljujic, Suzan Schneeweiss, Carrie Glanfield, Tania Principi

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2018
Typereview
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsCanadian Celiac Association
Fundersnot available
KeywordsStatistical process controlResuscitationMedical emergencyControl chartProcess (computing)MedicineMedical educationComputer scienceEmergency medicine

Abstract

fetched live from OpenAlex

STATEMENT: The rigorous evaluation of simulation in healthcare to improve resuscitations and team functioning can be challenging. Statistical process control (SPC) charts present a unique methodology to enable statistical rigor when evaluating simulation. This article presents a brief overview of SPC charts and its advantages over traditional before and after methodologies, followed by an exemplar using SPC to evaluate an in situ team training program with embedded interprofessional education sessions.

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)0.009
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.190
GPT teacher head0.569
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 designSimulation or modeling
Domainnot available
GenreReview

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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueSimulation in Healthcare The Journal of the Society for Simulation in HealthcareSame topicPatient Safety and Medication ErrorsFrench-language works237,207