Place of Death From Cancer in US States With vs Without Palliative Care Laws
Bibliographic record
Abstract
Importance: In the US, improving end-of-life care has become increasingly urgent. Some states have enacted legislation intended to facilitate palliative care delivery for seriously ill patients, but it is unknown whether these laws have any measurable consequences for patient outcomes. Objective: To determine whether US state palliative care legislation is associated with place of death from cancer. Design, Setting, and Participants: This cohort study with a difference-in-differences analysis used information about state legislation combined with death certificate data for 50 US states (from January 1, 2005, to December 31, 2017) for all decedents who had any type of cancer listed as the underlying cause of death. Data analysis for this study occurred between September 1, 2021, and August 31, 2022. Exposures: Presence of a nonprescriptive (relating to palliative and end-of-life care without prescribing particular clinician actions) or prescriptive (requiring clinicians to offer patients information about care options) palliative care law in the state-year where death occurred. Main Outcomes and Measures: Multilevel relative risk regression with state modeled as a random effect was used to estimate the likelihood of dying at home or hospice for decedents dying in state-years with a palliative care law compared with decedents dying in state-years without such laws. Results: This study included 7 547 907 individuals with cancer as the underlying cause of death. Their mean (SD) age was 71 (14) years, and 3 609 146 were women (47.8%). In terms of race and ethnicity, the majority of decedents were White (85.6%) and non-Hispanic (94.1%). During the study period, 553 state-years (85.1%) had no palliative care law, 60 state-years (9.2%) had a nonprescriptive palliative care law, and 37 state-years (5.7%) had a prescriptive palliative care law. A total of 3 780 918 individuals (50.1%) died at home or in hospice. Most decedents (70.8%) died in state-years without a palliative care law, while 15.7% died in state-years with a nonprescriptive law and 13.5% died in state-years with a prescriptive law. Compared with state-years without a palliative care law, the likelihood of dying at home or in hospice was 12% higher for decedents in state-years with a nonprescriptive palliative care law (relative risk, 1.12 [95% CI 1.08-1.16]) and 18% higher for decedents in state-years with a prescriptive palliative care law (relative risk, 1.18 [95% CI, 1.11-1.26]). Conclusions and Relevance: In this cohort study of decedents from cancer, state palliative care laws were associated with an increased likelihood of dying at home or in hospice. Passage of state palliative care legislation may be an effective policy intervention to increase the number of seriously ill patients who experience their death in such locations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".