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Record W2994981602 · doi:10.1177/0269216319875906

Economic evaluations of palliative care models: A systematic review

2019· review· en· W2994981602 on OpenAlexafffund
Christine Mathew, Amy T. Hsu, Michelle Prentice, Peter G. Lawlor, Kwadwo Kyeremanteng, Peter Tanuseputro, Vivian Welch

Bibliographic record

VenuePalliative Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsInstitut du Savoir MontfortOttawa HospitalUniversity of OttawaBruyère
FundersCanadian Institutes of Health Research
KeywordsPalliative careGeneralizability theoryChecklistMedicineSample size determinationMEDLINEEconomic evaluationHealth careNursingQuality of life (healthcare)Family medicineSystematic reviewPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Palliative care aims to improve quality of life by relieving physical, emotional, and spiritual suffering. Health system planning can be informed by evaluating cost and effectiveness of health care delivery, including palliative care. AIM: The objectives of this article were to describe and critically appraise economic evaluations of palliative care models and to identify cost-effective models in improving patient-centered outcomes. DESIGN: We conducted a systematic review and registered our protocol in PROSPERO (CRD42016053973). DATA SOURCES: A systematic search of nine medical and economic databases was conducted and extended with reference scanning and gray literature. Methodological quality was assessed using the Drummond checklist. RESULTS: We identified 12,632 articles and 5 were included. We included two modeling studies from the United States and England, and three economic evaluations from England, Australia, and Italy. Two studies compared home-based palliative care models to usual care, and one compared home-based palliative care to no care. Effectiveness outcomes included hospital readmission prevented, days at home, and palliative care symptom severity. All studies concluded that palliative care was cost-effective compared to usual care. The methodological quality was good overall, but three out of five studies were based on small sample sizes. CONCLUSION: Applicability and generalizability of evidence is uncertain due to small sample sizes, short duration, and limited modeling of costs and effects. Further economic evaluations with larger sample sizes are needed, inclusive of the diversity and complexity of palliative care populations and using patient-centered outcomes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0130.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.387
GPT teacher head0.526
Teacher spread0.139 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations64
Published2019
Admission routes2
Has abstractyes

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