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Record W2767259471 · doi:10.4018/ijhisi.2018010105

From E-Prescribing to Drug Management System

2017· article· en· W2767259471 on OpenAlexaff
Rola El Halabieh, Anne Beaudry, Robyn Tamblyn

Bibliographic record

VenueInternational Journal of Healthcare Information Systems and Informatics · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsTransition (genetics)Information systemManagement systemUser satisfactionDrugPsychologyStress (linguistics)BusinessOperations managementComputer sciencePsychiatryPolitical scienceHuman–computer interactionEngineering

Abstract

fetched live from OpenAlex

This study focuses on user reactions to the replacement of an information system they had been using. More specifically, a survey of physicians involved in the transition from an e-prescribing system to a new integrated drug management system was conducted. Data about physicians' level of stress induced by the system transition, satisfaction with the new system, and intention to continue to use the system, were collected as well as system usage logs before, during, and after the transition. Results indicate that physicians experiencing higher level of stress used the new system less during the transition as well as during the two months post-transition than their counterparts who reported lower level of stress. Although satisfaction with the new system was positively related to physicians' intention to use, it was not significantly related to actual usage. A discussion of the results and their implications for research and practice concludes the paper.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.005
Open science0.0020.000
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 head0.077
GPT teacher head0.390
Teacher spread0.312 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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