MétaCan
Menu
Back to cohort
Record W1952161065 · doi:10.5334/ijic.230

Providing supportive care to cancer patients: a study on inter-organizational relationships

2008· article· en· W1952161065 on OpenAlexaffabout
Kevin Brazil, Daryl Bainbridge, Jonathan Sussman, Timothy J. Whelan, Mary Ann O’Brien, Nancy Pyette

Bibliographic record

VenueInternational Journal of Integrated Care · 2008
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsService (business)Integrated careNursingBusinessKnowledge managementHealth carePsychologyMedicineMarketingComputer sciencePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Supportive cancer care (SCC) has historically been provided by organizations that work independently and possess limited inter-organizational coordination. Despite the recognition that SCC services must be better coordinated, little research has been done to examine inter-organizational relationships that would enable this goal. OBJECTIVE: The purpose of this study was to describe relationships among programs that support those affected by cancer. Through this description the study objective was to identify the optimal approach to coordinating SCC in the community. METHODS: Senior administrators in programs that provided care to persons and their families living with or affected by cancer participated in a personal interview. SETTING: South-central Ontario, Canada. STUDY POPULATION: administrators from 43 (97%) eligible programs consented to participate in the study. RESULTS: Network analysis revealed a diffuse system where centralization was greater in operational than administrative activities. A greater number of provider cliques were present at the operational level than the administrative level. Respondents identified several priorities to improve the coordination of cancer care in the community including: improving standards of care; establishing a regional coordinating body; increasing resources; and improving communication between programs. CONCLUSION: Our results point to the importance of developing a better understanding on the types of relationships that exist among service programs if effective integrated models of care are to be developed.

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)0.001
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 score0.313
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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

Citations7
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Integrated CareSame topicCancer survivorship and careFrench-language works237,207