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Record W4408019543 · doi:10.1136/jcp-2025-210065

If you provide them, they will come: an observational study of online pathology report access by patients at a large, academic, tertiary care hospital in Canada

2025· article· en· W4408019543 on OpenAlexaffabout
Jacob Ranot, Pedram Noghani, Deanna M. Rothwell, Jason K. Wasserman

Bibliographic record

VenueJournal of Clinical Pathology · 2025
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsTertiary careObservational studyMedicinePathologyFamily medicine

Abstract

fetched live from OpenAlex

AIMS: Patients of The Ottawa Hospital (TOH) are given immediate access to their pathology reports via an online patient portal. The purpose of this study was to determine how often patients accessed their reports, the sociodemographic and pathologic variables associated with access and the latency between sign out and access. METHODS: This retrospective cross-sectional observational study was conducted on the first 250 consecutive pathology reports published in 2023 from 10 different subspecialties in anatomical pathology at TOH. Data regarding date/time of report publication and access, as well as demographic data, and variables related to the individual report contents were extracted from the hospital's electronic health records. RESULTS: Of the 2500 patients included in this study, 1315 (52.6%) accessed their report online. Patients under 65 years of age, female patients and those residing within Ottawa were more likely to access their reports. Biopsies and reports with malignant diagnoses were accessed at higher rates than resections and benign cases, respectively. 463 (36.0%) patients accessed their reports within 24 hours; 822 (68.5%) accessed them within the first week. In 53% of cases, the patient accessed their report before the treating physician. CONCLUSIONS: These findings highlight that while over half of patients accessed their pathology reports online, significant differences in access rates were observed based on age, gender, location and report type. The high proportion of patients reviewing their reports before their treating physician underscores the need for patient-centred strategies to enhance understanding and support timely communication of results.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.105
GPT teacher head0.466
Teacher spread0.360 · 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 designObservational
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
Published2025
Admission routes2
Has abstractyes

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