MétaCan
Menu
Back to cohort
Record W2604943669

Enhancing family physician capacity to deliver quality palliative home care

2008· article· en· W2604943669 on OpenAlexvenueaboutno aff
Denise Marshall, Doris Howell, Kevin Brazil, Michelle Howard, Alan Taniguchi

Bibliographic record

VenueCanadian Family Physician · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative carePsychosocialNursingMedicinePsychological interventionGeneral partnershipFamily medicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM BEING ADDRESSED Family physicians face innumerable challenges to delivering quality palliative home care to meet the complex needs of end-of-life patients and their families. OBJECTIVE OF PROGRAM To implement a model of shared care to enhance family physicians’ ability to deliver quality palliative home care, particularly in a community-based setting. PROGRAM DESCRIPTION Family physicians in 3 group practices (N = 21) in Ontario’s Niagara West region collaborated with an interprofessional palliative care team (including a palliative care advanced practice nurse, a palliative medicine physician, a bereavement counselor, a psychosocial-spiritual advisor, and a case manager) in a shared-care partnership to provide comprehensive palliative home care. Key features of the program included systematic and timely identification of end-of-life patients, needs assessments, symptom and psychosocial support interventions, regular communication between team members, and coordinated care guided by outcome-based assessment in the home. In addition, educational initiatives were provided to enhance family physicians’ knowledge and skills. CONCLUSION Because of the program, participants reported improved communication, effective interprofessional collaboration, and the capacity to deliver palliative home care, 24 hours a day, 7 days a week, to end-of-life patients in the community.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.131
GPT teacher head0.355
Teacher spread0.224 · 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 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

Citations8
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Family PhysicianSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207