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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".