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Record W4384405989 · doi:10.51731/cjht.2023.693

Individuals’ Access to Medical Imaging Results via Patient Portals

2023· article· en· W4384405989 on OpenAlexaboutno aff
CADTH

Bibliographic record

VenueCanadian Journal of Health Technologies · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsnot available
Fundersnot available
KeywordsPatient portalHealth careMedical emergencyHealth informationMedical imagingInformation sharingMedicineBusinessWorld Wide WebComputer sciencePolitical scienceRadiology

Abstract

fetched live from OpenAlex


 Patient portals allow users to access, manage, and share their health information online.
 Patient portals are available in 6 provinces: Alberta, British Columbia, Saskatchewan, Ontario, Prince Edward Island, and Quebec.
 Patient portals in Canada are implemented at the provincial, regional, or clinic level of the health care system, and vary in the health data and features that are shared with users.
 Medical imaging reports are shared on portals in Alberta, Ontario, Quebec, and Saskatchewan. In Saskatchewan and Alberta, reports are available immediately, whereas Quebec has a 30-day embargo period. Ontario has an intention to enable patient portals to share medical images from provincial diagnostic imaging repositories in the future.
 A tailored approach may be considered when timing the release of medical imaging results due to concerns related to patient anxiety, especially for individuals waiting for diagnostic results of potentially life-threatening or serious conditions.
 Radiologists can use lay language in their reports and provide users with reliable sources of information to increase understanding of complex results. They may develop or take advantage of existing patient-friendly templates for sharing results on portals.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.748
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.389
Teacher spread0.333 · 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 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
Published2023
Admission routes1
Has abstractyes

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