MétaCan
Menu
Back to cohort
Record W2604562322 · doi:10.3233/978-1-61499-742-9-183

Interface Usability Across and Within EHR Vendors and Medical Settings: The Often Unexamined Need for Interface Similarities

2017· article· en· W2604562322 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in health technology and informatics · 2017
Typearticle
Languageen
FieldComputer Science
TopicPersona Design and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsUsabilityComputer scienceHuman–computer interactionInterface (matter)User interfaceUsability engineeringTransformative learningConceptual modelHealth careProcess (computing)Web usabilityKnowledge managementWorld Wide WebPsychology

Abstract

fetched live from OpenAlex

Usability of health information technology (HIT), if considered at all, is usually focused on individual providers, settings and vendors. However, in light of transformative models of healthcare delivery such as collaborative care delivery that crosses providers and settings, we need to think of usability as a collective and constantly emerging process. To address this new reality we develop a matrix of usability that spans several dimensions and contexts, incorporating differing vendors, user, settings, disciplines, and display configurations. The matrix, while conceptual, extends existing work by providing the means for discussion of usability issues and needs beyond one setting and one user type.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.058
GPT teacher head0.405
Teacher spread0.347 · 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