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Record W1950438251 · doi:10.7870/cjcmh-2015-001

Health Care Redesign for Responsive Behaviours—The Behavioural Supports Ontario Experience: Lessons Learned and Keys to Success

2015· article· en· W1950438251 on OpenAlexaffvenueabout
Iris Gutmanis, Matt Snyder, David Harvey, Loretta M. Hillier, J. Kenneth LeClair

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsQueen's UniversityAlzheimer Society of CanadaSt Joseph's Health Care
Fundersnot available
KeywordsCritical success factorProcess managementScale (ratio)Quality (philosophy)Health careKey (lock)CognitionNursingQuality of life (healthcare)PsychologyBusinessKnowledge managementMedicineComputer sciencePsychiatryPolitical scienceComputer security

Abstract

fetched live from OpenAlex

Our health care system is ill prepared for the growing number of older adults and their families/caregivers who live with responsive behaviours associated with cognitive impairment. Considering the burden of illness, quality of life issues, and escalating costs, system-wide redesign is warranted. The Behavioural Supports Ontario (BSO) project is a province-wide, regionally implemented, evidence-informed change strategy that utilizes quality improvement principles and knowledge translation best practices as critical enablers. This paper describes the project and key lessons learned in the implementation of this initiative that can be applied to other jurisdictions wishing to enable large-scale system redesign and sustainable system change.

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)0.018
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.091
Threshold uncertainty score0.662

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0070.007
Scholarly communication0.0060.004
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.611
GPT teacher head0.500
Teacher spread0.111 · 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

Citations24
Published2015
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Community Mental HealthSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207