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Record W2021866905 · doi:10.12927/hcq.2014.24022

Integrated Client Care for Frail Older Adults in the Community: Preliminary Report on a System-Wide Approach

2014· article· en· W2021866905 on OpenAlexaffabout
Jodeme Goldhar, Stacey Daub, Irfan A. Dhalla, Philip Ellison, Dipti Purbhoo, Samir K. Sinha

Bibliographic record

VenueHealthcare Quarterly · 2014
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsSinai Health SystemRegistered Nurses' Association of OntarioHome and Community Care Support Services
Fundersnot available
KeywordsIntegrated careBest practiceKey (lock)Quality (philosophy)Health careNursingBusinessProcess managementHealthcare systemSystem integrationGerontologyMedicinePublic relationsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The Toronto Central Community Care Access Centre is leading a collaborative local health integration network systemic change initiative to implement and evaluate a practical model of integrated care for older adults with complex needs. The approach is embedded in the community where older adults and their families live and is designed to first and foremost improve the quality of care while ultimately bending the cost curve. The model is leveraging and aligning existing system resources by bringing together sectors from across the health system to create ways of working that build capacity in the system to be more responsive to this population. Outcomes to date will be discussed and next steps described. The secondary goal was to understand the key elements of this integration that can be scaled locally and across the province.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0030.002
Open science0.0020.012
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.035
GPT teacher head0.397
Teacher spread0.362 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2014
Admission routes2
Has abstractyes

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