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Record W3215323588 · doi:10.12927/hcpol.2021.26659

Comparing the Attainment of the Patient’s Medical Home Model across Regions in Three Canadian Provinces: A Cross-Sectional Study

2021· article· en· W3215323588 on OpenAlexafffundvenueabout
Sabrina T. Wong, Sharon Johnston, Fred Burge, Mehdi Ammi, John Campbell, Alan Katz, Ruth Martin‐Misener, Sandra Peterson, Manpreet Thandi, Jeannie Haggerty, William Hogg

Bibliographic record

VenueHealthcare policy · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill UniversityVancouver Coastal HealthUniversity of ManitobaMcGill University Health CentreCarleton UniversityDalhousie UniversityUniversity of OttawaManitoba HealthInstitut du Savoir MontfortUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsPortraitPrimary careStrengths and weaknessesBaseline (sea)GeographyPsychologyRegional scienceMedicinePolitical scienceFamily medicineSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this work was to show the feasibility of providing a comprehensive portrait of regional primary care performance. METHODS: The TRANSFORMATION study used a mixed-methods concurrent study design where we analyzed survey data and case studies. Data were collected in British Columbia, Ontario and Nova Scotia. Patient's Medical Home (PMH) pillar scores were created by calculating mean clinic-level scores across regions. Scores and qualitative themes were compared. RESULTS: Participation included 86 practices (n = 1,929 patients; n = 117 clinicians). Regions had differential attainment towards PMH orientation with respect to infrastructure; community adaptiveness and accountability; and patient and family partnered care. The lowest PMH attainment for all regions were observed in connected care; accessible care; measurement, continuous quality improvement and research; and training, education and continuing professional development. CONCLUSIONS: Comprehensive performance reporting that draws on multiple data sources in primary care is possible. Regional portraits highlighting many of the key pillars of a PMH approach to primary care show that despite differences in policy contexts, achieving a PMH remains elusive.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.150
GPT teacher head0.482
Teacher spread0.333 · 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 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

Citations9
Published2021
Admission routes4
Has abstractyes

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