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Record W1976357776 · doi:10.3109/13561820.2014.984019

Measuring horizontal integration among health care providers in the community: an examination of a collaborative process within a palliative care network

2014· article· en· W1976357776 on OpenAlexaff
Daryl Bainbridge, Kevin Brazil, Paul Krueger, Jenny Ploeg, Alan Taniguchi, Julie Darnay

Bibliographic record

VenueJournal of Interprofessional Care · 2014
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsCARE CanadaMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsRespondentAgency (philosophy)Palliative careWorkloadHealth careNursingProcess (computing)PsychologyMedicineMedical educationSociologyComputer science

Abstract

fetched live from OpenAlex

In many countries formal or informal palliative care networks (PCNs) have evolved to better integrate community-based services for individuals with a life-limiting illness. We conducted a cross-sectional survey using a customized tool to determine the perceptions of the processes of palliative care delivery reflective of horizontal integration from the perspective of nurses, physicians and allied health professionals working in a PCN, as well as to assess the utility of this tool. The process elements examined were part of a conceptual framework for evaluating integration of a system of care and centred on interprofessional collaboration. We used the Index of Interdisciplinary Collaboration (IIC) as a basis of measurement. The 86 respondents (85% response rate) placed high value on working collaboratively and most reported being part of an interprofessional team. The survey tool showed utility in identifying strengths and gaps in integration across the network and in detecting variability in some factors according to respondent agency affiliation and profession. Specifically, support for interprofessional communication and evaluative activities were viewed as insufficient. Impediments to these aspects of horizontal integration may be reflective of workload constraints, differences in agency operations or an absence of key structural features.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.097
GPT teacher head0.424
Teacher spread0.327 · 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 designQualitative
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

Citations19
Published2014
Admission routes1
Has abstractyes

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