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Record W2128122302 · doi:10.1258/hsmr.2008.008001

Management of complex chronic disease: facing the challenges in the Canadian health-care system

2008· article· en· W2128122302 on OpenAlexaffabout
Peter Tsasis, Jatinder Bains

Bibliographic record

VenueHealth Services Management Research · 2008
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsBridgepoint Active HealthcareYork University
Fundersnot available
KeywordsHealth careBusinessMedicineChronic diseaseChronic careDiseaseHealth policyNursingDisease managementHRHISHealth care deliveryInvestment (military)Economic growthFamily medicinePublic healthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

This paper discusses the challenges that those living with complex chronic disease present to the Canadian health-care system. The literature suggests home care and the management of complex chronic disease can together ease many of the present and future pressures facing the health-care system in dealing with this new health-care phenomenon. A review of current literature and dialogue with key informants reveals that the current level of investment and the present policy environment are not sustainable to support the health-care system. In this paper, changes to policy and resource allocation to the home care sector are suggested to help manage complex chronic disease and thus improve the effectiveness of the Canadian health-care system. A case is made for a reorganization and increased commitment to the home care sector for a more efficient and patient-centred health-care delivery system.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.909
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0130.007
Scholarly communication0.0090.003
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.233
GPT teacher head0.440
Teacher spread0.207 · 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 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

Citations34
Published2008
Admission routes2
Has abstractyes

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