Predictors of Posthospital Transitions of Care in Patients With Advanced Cancer
Bibliographic record
Abstract
Purpose Patients with advanced cancer experience potentially burdensome transitions of care after hospitalizations. We examined predictors of discharge location and assessed the relationship between discharge location and survival in this population. Methods We conducted a prospective study of 932 patients with advanced cancer who experienced an unplanned hospitalization between September 2014 and March 2016. Upon admission, we assessed patients' physical symptoms (Edmonton Symptom Assessment System) and psychological distress (Patient Health Questionnaire-4). The primary outcome was discharge location (home without hospice, postacute care [PAC], or hospice [any setting]). The secondary outcome was survival. Results Of 932 patients, 726 (77.9%) were discharged home without hospice, 118 (12.7%) were discharged to PAC, and 88 (9.4%) to hospice. Those discharged to PAC and hospice reported high rates of severe symptoms, including dyspnea, constipation, low appetite, fatigue, depression, and anxiety. Using logistic regression, patients discharged to PAC or hospice versus home without hospice were more likely to be older (odds ratio [OR], 1.03; 95% CI, 1.02 to 1.05; P < .001), live alone (OR, 1.95; 95% CI, 1.25 to 3.02; P < .003), have impaired mobility (OR, 5.08; 95% CI, 3.46 to 7.45; P < .001), longer hospital stays (OR, 1.15; 95% CI, 1.11 to 1.20; P < .001), higher Edmonton Symptom Assessment System physical symptoms (OR, 1.02; 95% CI, 1.003 to 1.032; P < .017), and higher Patient Health Questionnaire-4 depression symptoms (OR, 1.13; 95% CI, 1.01 to 1.25; P < .027). Patients discharged to hospice rather than PAC were more likely to receive palliative care consultation (OR, 4.44; 95% CI, 2.12 to 9.29; P < .001) and have shorter hospital stays (OR, 0.84; 95% CI, 0.77 to 0.91; P < .001). Patients discharged to PAC versus home had lower survival (hazard ratio, 1.53; 95% CI, 1.22 to 1.93; P < .001). Conclusion Patients with advanced cancer who were discharged to PAC facilities and hospice had substantial physical and psychological symptom burden, impaired physical function, and inferior survival compared with those discharged to home. These patients may benefit from interventions to enhance their quality of life and care.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".