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Record W2613084331 · doi:10.9778/cmajo.20160097

Patient-Centred Innovations for Persons with Multimorbidity: funded evaluation protocol

2017· article· en· W2613084331 on OpenAlexafffundvenueabout
Moira Stewart, Martin Fortin

Bibliographic record

VenueCMAJ Open · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsCentre de Santé et de Services Sociaux de ChicoutimiUniversité de SherbrookeWestern University
FundersCanadian Institutes of Health ResearchServierNovo NordiskSanofiEli Lilly and Company
KeywordsMedicineHealth careProtocol (science)Randomized controlled trialFamily medicineNursingQuality of life (healthcare)MultimorbidityAlternative medicineChronic disease

Abstract

fetched live from OpenAlex

BACKGROUND: The high prevalence of multimorbidity necessitates rethinking of the health care system. The overarching goal of the Patient-Centred Innovations for Persons with Multimorbidity program is to build on existing structures and find and evaluate patient-centred innovations relevant to multimorbidity. METHODS: We describe the protocol for a proposed multijurisdictional (Quebec and Ontario) concurrent triangulation mixed-methods study. In both provinces, a qualitative descriptive study will be used to explore innovations in patient-centred multimorbidity care. Two randomized controlled trials, 1 in either province, will evaluate the innovations in a wait-list-controlled design using patient-reported outcomes. An additional control group, matched on age, sex, enrolment/index date (± 3 mo) and propensity score, will be created with the use of health administrative data. Patients will be 18-80 years of age and will have 3 or more chronic conditions. The innovations will have elements of relevance to multimorbidity care, patient-centred partnerships and integration of care. The primary outcome measures will be 2 patient-reported outcomes: patient education and self-efficacy. Secondary outcomes will include patient-reported health status, quality of life, psychological distress and health behaviours, and costs of care. INTERPRETATION: ClinicalTrials.gov, no NCT02789800 (Quebec Trial), NCT02742597 (Ontario Trial).

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: Not applicable
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.664
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.221
GPT teacher head0.442
Teacher spread0.220 · 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
GenreProtocol

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

Citations31
Published2017
Admission routes4
Has abstractyes

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