Palliative Care as a Component of High-Value and Cost-Saving Care During Hospitalization for Metastatic Cancer
Bibliographic record
Abstract
PURPOSE Randomized controlled trials have demonstrated that palliative care (PC) can improve quality of life and survival for outpatients with advanced cancer, but there are limited population-based data on the value of inpatient PC. We assessed PC as a component of high-value care among a nationally representative sample of inpatients with metastatic cancer and identified hospitalization characteristics significantly associated with high costs. METHODS Hospitalizations of patients 18 years and older with a primary diagnosis of metastatic cancer from the National Inpatient Sample from 2010 to 2019 were analyzed. We used multivariable mixed-effects logistic regression to assess medical services, patient demographics, and hospital characteristics associated with higher charges billed to insurance and hospital costs. Generalized linear mixed-effects models were used to determine cost savings associated with provision of PC. RESULTS Among 397,691 hospitalizations from 2010 to 2019, the median charge per admission increased by 24.9%, from $44,904 in US dollars (USD) to $56,098 USD, whereas the median hospital cost remained stable at $14,300 USD. Receipt of inpatient PC was associated with significantly lower charges (odds ratio [OR], 0.62 [95% CI, 0.61 to 0.64]; P < .001) and costs (OR, 0.59 [95% CI, 0.58 to 0.61]; P < .001). Factors associated with high charges were receipt of invasive medical ventilation ( P < .001) or systemic therapy ( P < .001), Hispanic patients ( P < .001), young age (18-49 years, P < .001), and for-profit hospitals ( P < .001). PC provision was associated with a $1,310 USD (–13.6%, P < .001) reduction in costs per hospitalization compared with no PC, independent of the receipt of invasive care and age. CONCLUSION Inpatient PC is associated with reduced hospital costs for patients with metastatic cancer, irrespective of age and receipt of aggressive interventions. Integration of inpatient PC may de-escalate costs incurred through low-value inpatient interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".