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Record W2942677052 · doi:10.1093/pch/19.6.e35-150

153: Resident Attitudes and Adherence to I-PASS: A Qualitative Study

2014· article· en· W2942677052 on OpenAlexaff
Maitreya Coffey, Kelly Thomson, AJ Starmer, CP Landrigan, I-PASS Qualitative Study Group

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMnemonicThematic analysisHandoverCoding (social sciences)MedicineQualitative researchPatient safetyFocus groupMedical educationQualitative propertyEveningNursingPsychologyComputer scienceHealth care

Abstract

fetched live from OpenAlex

The main I-PASS Study assesses the effectiveness of a Handoff Bundle (team training, verbal mnemonic, and electronic written handoff tool) at nine residency programs using quantitative data on patient safety outcomes as well as efficiency and provider satisfaction. The objective of this ancillary qualitative study was to describe in detail the resident experience of I-PASS implementation, in general and with respect to the individual components, in order to inform future refinements and implementation strategies. Focus groups with residents (n=54); and semi-structured interviews with faculty (n=28) and other personnel (n=10) were conducted at eight of nine I-PASS sites. A structured codebook was developed to facilitate descriptive coding of transcripts, and data were synthesized and summarized using content analysis. Triangulation was employed by comparing findings across data sources. Residents generally accept I-PASS to be a ‘gold standard’ form of handoff and value learning a structured approach. Junior residents and some senior residents feel more secure using a structured format and most recognize that the program enhances handoff quality and patient safety. Efficiency was the most common factor cited when residents expressed concern about I-PASS. They regard it as neither necessary nor feasible to follow I-PASS for every patient and situation. Across all sites, residents report adhering to I-PASS when observed, but adhering selectively in usual practice. Residents were more likely to adhere with complex patients, unfamiliar teams, and evening vs. morning handoff. They also report using elements of the I-PASS mnemonic variably, with “synthesis by receiver” rarely used outside the context of observation. Anything perceived to lengthen handoff was unwelcome. Most residents value the computerized written handoff tool, but at sites with significant tool usability problems, dissatisfaction extended to the whole I-PASS program. The degree to which resident feedback was sought and acted upon moderated this. Perceptions of the faculty role varied. Residents generally understood that faculty have different handoff needs and practices, so did not perceive faculty as hypocritical if they did not adhere to I-PASS themselves. The experiences of observation and feedback were mixed. Residents reported variation in faculty feedback styles; some residents found it constructive while others found it ‘nitpicky’. Residents felt that the I-PASS program improved safety, but had concerns about efficiency. Optimizing computerized handoff tools, efficiency of verbal handoffs, and feedback to residents will be important in future refinements and implementation efforts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.392
Teacher spread0.362 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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