Rurality, Health Care Resource Use, and Care Trajectories in Patients With Head and Neck Cancer
Bibliographic record
Abstract
Importance: Head and neck cancer (HNC) epidemiology varies geographically, and rural populations (typically less affluent) may face barriers accessing cancer care, which could lead to worse outcomes. Objective: To compare health care resource use between patients with HNC living in urban and rural areas. Design, Setting, and Participants: Retrospective cohort study in Alberta, Canada. Participants were adult patients (aged ≥18 years) diagnosed with HNC with at least 1 year of posttreatment follow-up between January 2012 and September 2020. Data were analyzed from August to September 2024. Exposure: Rural location of residence at HNC diagnosis, defined using the forward sortation area of the patients' postal code. Main Outcomes and Measures: The primary outcomes were health care resource use and patient care trajectories, including hospital length of stay, 30-day hospital readmissions, emergency department visits, time from diagnosis to first treatment, first type of practitioner seen after hospital discharge, and most common practitioner-to-practitioner transitions. Results: The cohort included 2189 patients with a median (IQR) age of 63 (55-71) years, who were mostly men (1557 patients [71.1%]) with stage IV cancer (1149 patients [52.5%]) of the tongue (640 patients [29.2%]), of which 375 (17.1%) lived in a rural area. There was no difference in cumulative hospital length of stay between urban and rural patients; however, male patients living in rural areas had a longer surgical hospital length of stay than male patients living in urban areas (incidence rate ratio, 1.24; 95% CI, 1.03-1.50). Patients living in rural areas had more 30-day hospital readmissions (63 patients [16.8%] vs 183 patients [10.1%]) and emergency department visits (median [IQR], 8 [3-17] vs 4 [2-9]) than their urban counterparts. Time to first treatment was longer in patients living in rural areas compared with patients living in urban areas (median [IQR], 64 [46-95] days vs 57 [40-84] days). Patients living in rural areas without comorbid conditions had greater odds of being discharged directly to the care of a general practitioner after a hospital stay than urban patients (odds ratio, 1.97; 95% CI, 1.23-3.15). Conclusions and Relevance: In this cohort study of patients with HNC, living in rural areas was associated with higher health care resource use than patients living in urban areas. Recommendations specific to patients with HNC living in rural areas may be warranted given these differences.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".