Opportunities for improved end-of-life (EOL) care for adult patients with advanced cancer: Results of a longitudinal assessment of care provided by Quality Oncology Practice Initiative (QOPI) participants.
Bibliographic record
Abstract
132 Background: End of life care of patients with advanced cancer has received recent attention because of evidence of widespread variation in utilization of aggressive therapies and interventions and possible suboptimal use of palliative care and hospice services. QOPI, the ASCO sponsored quality assessment program, has been available to all United States physician members since January 2006 and has assessed EOL care since its inception. The current analysis explores whether the increased national focus on EOL and increased availability of palliative care and hospice services has resulted in improvements in EOL care as reported by QOPI participants. Methods: Data was aggregated across all EOL care quality measures for 9 sequential semi-annual QOPI collection periods from 2008 through 2012. Trends were analyzed among rates of eligible patients related to hospice enrollment and timing of enrollment, palliative care referrals, discussions about hospice and palliative care, and chemotherapy administration at the end of life. The Cochran-Armitage trend test was performed to determine the significance of trends and differences in measure performance over time. Results: From Fall 2008 to Fall 2012, the rate of hospice enrollment for appropriate patients improved by 7.4% [51.8% to 59.2%; p<0.0001] and the rate of hospice enrollment or palliative care referral improved by 5.6% [63.3% to 68.9%; p<0.0001]. Modest improvements were seen in the rates of hospice enrollment more than 3 and 7 days before death [2.8%, 2.6%], discussion of hospice or palliative care with patients not referred for these services within the last 2 months of life [2.7% increase; 19% to 21.7%], and chemotherapy administration within the last 2 weeks of life [2.4% improvement from 13.7% to 11.3%]. Conclusions: Despite modest increases in the rate of hospice enrollment and palliative care referrals over time, EOL care for adult patients with cancer associated with QOPI practices remains suboptimal. Opportunities exist to increase more meaningful participation in hospice and palliative care and to reduce exposure to chemotherapy near death.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".