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Record W1877715241 · doi:10.5334/ijic.2241

Continuing efforts to integrate care can benefit from cross-jurisdictional comparisons

2015· article· en· W1877715241 on OpenAlexaff
Walter P. Wodchis, Anna Dixon, Geoff Anderson

Bibliographic record

VenueInternational Journal of Integrated Care · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntegrated careHealth careBusinessNursingPublic relationsMedicinePolitical science

Abstract

fetched live from OpenAlex

Despite its theoretical appeal, integrated care remains a new frontier for health and social care systems in many countries. A key motivation for increasing the integration of a range of health care services with socialor community-based services is the imperative to improve the patient experience, particularly for individuals with ongoing multiple and complex health care and functional needs. To meet these needs they receive care from many different providers and often they feel they are bouncing around in an uncoordinated system that requires them to repeatedly tell their stories but that fails to provide a clearly articulated coordinated plan of care to help them manage their conditions. A key to improving the patient experience, care coordination and outcomes, is the need to address failures associated with low-fidelity of information sharing among providers, as patients transition from one provider to another. Failure to share information on treatment goals and therapies almost inevitably results in an incoherent treatment plan that often is duplicative or self-defeating and that in some cases causes more harm than good. Along with improving the patient experience, integrated care can increase the system-level efficiency of treatment and lower costs. Bringing multiple services into a coordinated network where information is centrally held and shared supports coordinated scheduling, shared access to essential information and reduction in duplication of diagnostic tests. In theory integrated care can improve patient experience and outcomes while reducing costs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.020
GPT teacher head0.296
Teacher spread0.276 · 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 designNot applicable
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

Citations1
Published2015
Admission routes1
Has abstractyes

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