MétaCan
Menu
Back to cohort
Record W2396646367 · doi:10.1177/082585971302900304

The Size, Share, and predictors of Publicly Financed Healthcare Costs in the Home Setting over the Palliative Care Trajectory: A Prospective Study

2013· article· en· W2396646367 on OpenAlexafffund
Huamin Chai, Denise N. Guerriere, Brandon Zagorski, Julia Kennedy, Peter C. Coyte

Bibliographic record

VenueJournal of Palliative Care · 2013
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPalliative carePsychological interventionWarrantHealth careMedicineFamily caregiversLogistic regressionEnd-of-life careService (business)Actuarial scienceGerontologyNursingBusinessFinanceEconomicsMarketingEconomic growth

Abstract

fetched live from OpenAlex

INTRODUCTION: The increasing attention on home-based service provision for end-of-life care has resulted in greater financial demands being placed on family caregivers. The purpose of this study was to assess publicly financed costs within a home-based setting from a societal perspective. METHODS: A prospective cohort study design was employed. In all, 129 caregivers of palliative care patients were interviewed biweekly for a total of 667 interviews. Multiple regression analysis (log-linear regression and seemingly unrelated regression [SUR]) was conducted. RESULTS: While publicly financed costs accounted for 20 percent of the full economic costs and increased with proximity to death, 76.7 percent of costs were borne by patients' caregivers in the form of unpaid caregiving. The share of publicly financed healthcare costs was driven by patients' and caregivers' sociodemographic and clinical characteristics. CONCLUSION: These findings warrant affording greater attention to policies and interventions intended to reduce the economic burden on palliative patients and their caregivers.

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)0.002
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 score0.149
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.057
GPT teacher head0.385
Teacher spread0.328 · 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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Palliative CareSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207