Preferred versus Actual Place of Care and Factors Associated with Home Discharge among Korean Patients with Advanced Cancer: A Retrospective Cohort Study
Bibliographic record
Abstract
Respecting the preference for a place of care is essential for advance care planning in patients with advanced cancer. This retrospective study included adult patients with cancer referred to an inpatient palliative care consultation team at a tertiary acute care hospital in South Korea between April 2019 and December 2020. Patients’ preference for place of care and demographic and clinical factors were recorded, and the actual discharge locations were categorized as home or non-home. Patients discharged home but with unintended hospital visits within 2 months were also investigated. Of the 891 patients referred to the palliative care consultation team, 210 (23.6%) preferred to be discharged home. Among them, 113 (53.8%) were discharged home. No significant differences were found between patients who preferred home discharge and those who did not. Home discharge was higher among female patients (p = 0.04) and lower in those with poor oral intake (p < 0.001) or dyspnea (p = 0.02). Of the 113 patients discharged home, 37 (32.8%) had unintended hospital visits within 2 months. Approximately one-quarter of hospitalized patients with advanced cancer preferred to be discharged home, but only half of them received the home discharge. To meet patients’ preferences for end-of-life care, individual care planning considering relevant factors is necessary.
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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 | 0.001 |
| 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 | 0.001 |
| 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".