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Record W2130164921 · doi:10.12927/hcpap..17353

Implementing Home Care in Canada: Four Critical Elements

2000· letter· en· W2130164921 on OpenAlexaffvenueabout
Blair G. Richardson

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2000
Typeletter
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsHealth carePublic healthEquity (law)Population healthLibrary scienceHealth policyPublic policyPolitical scienceSociologyMedicineNursing

Abstract

fetched live from OpenAlex

While MacAdam proposes a "national approach to home care#8221; the obstacles to this are well known and substantial. They are the likely cost and the limitations of the federal government s role in healthcare. Building on MacAdam's assessment, this paper outlines four problems embedded in the various home-care service delivery models in Canada: the lack of factual client outcome information to support decision-making, the limited client choice of provider, the perverse incentive of fee for service and the bias against the for-profit provider. The paper proposes that the assessment, classification and measurement of outcomes for every recipient of home-care services be standardized using a proven assessment instrument, such as OASIS-B or MDS-HC, by healthcare professionals certified in its use. The resulting information would be captured in a regional database and available for analysis and research. CIHI would be contracted to manage a national database and to fund the training and certification of assessors. The paper proposes a new service delivery and funding model, utilizing standard client outcome information, different roles for regional health authorities and service providers, and a prospective payment mechanism replacing fee for service. A national home care program may be an elusive dream, but that shouldn't stop experimentation, evaluation and improvement.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.378
Teacher spread0.291 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2000
Admission routes3
Has abstractyes

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