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Record W2995846315 · doi:10.12927/hcq.2019.26018

Implementation of a Physician–Patient Attachment Initiative in Alberta

2019· article· en· W2995846315 on OpenAlexaffvenueabout
Lisa L. Cook, Tobias Gelber, Charles M. Cook

Bibliographic record

VenueHealthcare Quarterly · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsPrimary careNursingMedical homeBest practiceDelivery systemMedicinePsychologyMedical educationFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Attachment to a primary care physician (PCP) is a foundational component of the Patient's Medical Home. Yet how can attachment exist in a system that does not limit where patients seek care? This article describes a top-down approach with the ideologies of a bottom-up collaborative to address attachment within an Alberta primary care network. The steps taken to reduce the number of patients listed on multiple PCP panels from 27% to 4% will be described. Learnings from this initiative suggest that direct involvement with providers, coupled with engaged physician leadership, can create a local system of information delivery that supports the attachment of patients to their most responsible PCP.

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)0.007
metaresearch head score (Gemma)0.007
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: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.003
Scholarly communication0.0030.001
Open science0.0030.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.043
GPT teacher head0.444
Teacher spread0.401 · 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

Citations3
Published2019
Admission routes3
Has abstractyes

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