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Record W3165625139 · doi:10.3233/shti210260

Usage of Digital Tools to Access Primary Care in Quebec: An Environmental Scan

2021· book-chapter· en· W3165625139 on OpenAlexaffabout
J. Y. Lapointe, Janine Badr, Aude Motulsky

Bibliographic record

VenueStudies in health technology and informatics · 2021
Typebook-chapter
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsWork (physics)Health carePrimary careBusinessMedical emergencyComputer scienceMedicinePolitical scienceEngineeringFamily medicine

Abstract

fetched live from OpenAlex

Timely access to care is a persistent challenge for health care systems. Providing the right care to the right patient at the right time is important to reduce inappropriate use and improve the performance of healthcare services. The complexity of accessing primary care contributes to the high usage of emergency rooms for not-urgent conditions. Many digital tools try to offer a better access to care for patients and reduce ER overuse. This environmental scan of the digital tools available in Quebec identifies those digital tools and some of their limitations. The results reveal the complexity of mobilizing digital tools in the healthcare sector and highlight the need for all stakeholders to work together to enhance access to care.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.002
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 head0.148
GPT teacher head0.468
Teacher spread0.320 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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