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How Do Patients Perceive Electronic Documentation at the Bedside?

2006· article· en· W2014295736 on OpenAlexaff
Vico Dagnone, Rosemary Wilson, David Goldstein, John A. C. Murdoch, Michael J. Rimmer, Elizabeth G. VanDenKerkhof

Bibliographic record

VenueJournal for Healthcare Quality · 2006
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsDocumentationMedical emergencyAffect (linguistics)Medical recordQuality (philosophy)MedicineElectronic health recordHealth recordsHealth careElectronic medical recordPatient carePsychologyNursingComputer scienceCommunication

Abstract

fetched live from OpenAlex

Electronic patient records provide an opportunity for real-time access to patient information at the bedside, which has the potential to improve healthcare quality because it would increase efficiency and facilitate best practice. Patients in this study reported that portable computers used at the bedside did not affect the clinician-patient relationship. Many patients thought that the technology was a valuable tool and that it could foster an efficient hospital atmosphere and promote reliable and accurate medical documentation.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.071
GPT teacher head0.495
Teacher spread0.424 · 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 designNot applicable
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

Citations15
Published2006
Admission routes1
Has abstractyes

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