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Record W2611265287 · doi:10.3747/co.24.3447

The Role of Family Physicians in Cancer Care: Perspectives of Primary and Specialty Care Providers

2017· article· en· W2611265287 on OpenAlexafffundvenueabout
Julie Easley, Baukje Miedema, Mary Ann O’Brien, June Carroll, Donna Manca, Fiona Webster, Eva Grunfeld

Bibliographic record

VenueCurrent Oncology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of AlbertaUniversity of TorontoSinai Health SystemDalhousie University
FundersCanadian Institutes of Health Research
KeywordsMedicinePrimary careSpecialtyFamily medicineAlternative medicineNursingCancerInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Currently, the specific role of family physicians (fps) in the care of people with cancer is not well defined. Our goal was to explore physician perspectives and contextual factors related to the coordination of cancer care and the role of fps. METHODS: Using a constructivist grounded theory approach, we conducted telephone interviews with 58 primary and cancer specialist health care providers from across Canada. RESULTS: The participants-21 fps, 15 surgeons, 12 medical oncologists, 6 radiation oncologists, and 4 general practitioners in oncology-were asked to describe both the role that fps currently play and the role that, in their opinion, fps should play in the future care of cancer patients across the cancer continuum. Participants identified 3 key roles: coordinating cancer care, managing comorbidities, and providing psychosocial care to patients and their families. However, fps and specialists discussed many challenges that prevent fps from fully performing those roles: ■ The fps described communication problems resulting from not being kept "in the loop" because they weren't copied on patient reports and also the lack of clearly defined roles for all the various health care providers involved in providing care to cancer patients.■ The specialists expressed concerns about a lack of patient access to fp care, leaving specialists to fill the care gaps. The fps and specialists both recommended additional training and education for fps in survivorship care, cancer screening, genetic testing, and new cancer treatments. CONCLUSIONS: Better communication, more collaboration, and further education are needed to enhance the role of fps in the care of cancer patients.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.107
GPT teacher head0.500
Teacher spread0.393 · 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

Citations73
Published2017
Admission routes4
Has abstractyes

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