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Record W3034122735 · doi:10.1097/mlr.0000000000001320

Cost-effectiveness of Investment in End-of-Life Home Care to Enable Death in Community Settings

2020· article· en· W3034122735 on OpenAlexaffabout
Sarina R. Isenberg, Peter Tanuseputro, Sarah Spruin, Hsien Seow, Russell Goldman, Kednapa Thavorn, Amy T. Hsu

Bibliographic record

VenueMedical Care · 2020
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcMaster UniversityOttawa HospitalBruyèreUniversity of OttawaLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
Fundersnot available
KeywordsEnd-of-life careInvestment (military)BusinessCost effectivenessActuarial scienceMedicineNursingGerontologyRisk analysis (engineering)Palliative carePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Many people with terminal illness prefer to die in home-like settings-including care homes, hospices, or palliative care units-rather than an acute care hospital. Home-based palliative care services can increase the likelihood of death in a community setting, but the provision of these services may increase costs relative to usual care. OBJECTIVE: The aim of this study was to estimate the incremental cost per community death for persons enrolled in end-of-life home care in Ontario, Canada, who died between 2011 and 2015. METHODS: Using a population-based cohort of 50,068 older adults, we determined the total cost of care in the last 90 days of life, as well as the incremental cost to achieve an additional community death for persons enrolled in end-of-life home care, in comparison with propensity score-matched individuals under usual care (ie, did not receive home care services in the last 90 days of life). RESULTS: Recipients of end-of-life home care were nearly 3 times more likely to experience a community death than individuals not receiving home care services, and the incremental cost to achieve an additional community death through the provision of end-of-life home care was CAN$995 (95% confidence interval: -$547 to $2392). CONCLUSION: Results suggest that a modest investment in end-of-life home care has the potential to improve the dying experience of community-dwelling older adults by enabling fewer deaths in acute care hospitals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.164
GPT teacher head0.422
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2020
Admission routes2
Has abstractyes

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