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Record W2904311898 · doi:10.1016/j.hpe.2018.12.001

Enhancing skills in patient care documentation and transfer of care: An example of intra-professional collaboration across pharmacy schools through video-conferencing

2018· article· en· W2904311898 on OpenAlexaffabout
Sherilyn K. D. Houle, Theresa L. Charrois

Bibliographic record

VenueHealth Professions Education · 2018
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of AlbertaUniversity of Waterloo
Fundersnot available
KeywordsDocumentationPharmacyMedical educationPerspective (graphical)PsychologyVideoconferencingMedicineNursingMultimediaComputer science

Abstract

fetched live from OpenAlex

Documentation of care is a challenging skill to teach, especially when assessments are performed by individuals with familiarity with the case being documented. We designed an activity utilizing peer-review of documentation by students unfamiliar with the patient case, to better replicate real-life interprofessional communications. Pharmacy students from the University of Waterloo and the University of Alberta were provided anonymized notes from a group of students at the other institution. Groups met via video-conference to provide feedback and ask questions about the notes they received. Students were surveyed on their confidence and skills in documentation prior to and following the activity, and also submitted reflections on the experience, which were assessed using qualitative content analysis. Improvements in students’ self-perceived documentation skills showed slight improvement after versus before the activity; however, student reflections were highly positive and showed a change in perspective from documentation being considered something to be done for the documenter׳s personal reference, to something that is invaluable to seamless care transitions between professionals and care settings. Students commonly receive feedback from peers and instructors; however, educators should consider the added benefit of offering feedback from the perspective of individuals unfamiliar with the patient case and from different institutions.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.467
Teacher spread0.436 · 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.

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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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