Delays in access to palliative care services among cancer patients in South Texas.
Bibliographic record
Abstract
215 Background: The growing support for integrated palliative and cancer care resulted in the American Society of Clinical Oncology’s new recommendation which states patients “with advanced cancer should receive dedicated palliative care services, early in the disease course, concurrent with active treatment.” Unfortunately, timely access to palliative services remains an issue for cancer patients and centers. The aim of this project is to evaluate how socioeconomic factors impact palliative access for patients in South Texas. Methods: During a 6-month period, patients in oncology clinics completed the Edmonton Symptom Assessment System questionnaire. Scores reaching a predetermined threshold resulted in a provider alert to consider referral to palliative services. We examine time to initial palliative appointment after referral and compare time to visit based on location of palliative services determined by insurance coverage. Results: During our study period, providers referred 47 unique patients with 27 patients eligible to receive care at the University of Texas Medicine System (Group A) and 20 patients qualified for care at the University Hospital System providing services to under-insured and safety net patients (Group B). Of the 47 referred patients, 27 (57%) patients were offered an appointment and only 17 patients (36%) actually had a palliative care visit (13/27 (48%) Group A patients and 4/20 (20%) Group B patients). On average, Group B patients had 25.2 days longer wait times to palliative visits compared to Group A patients. Conclusions: This investigation revealed a discrepancy between referral and actual receipt of care. While this study is limited by a small sample, data suggests that under-insured oncology patients may have significantly different access to palliative services which may impact the quality of cancer care. [Table: see text]
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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 | 0.001 |
| 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) | 0.003 | 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".