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Record W4388721023 · doi:10.1370/afm.22.s1.5124

Family physicians who provide comprehensive care to a group of patients over the long term: A study of key factors

2023· article· en· W4388721023 on OpenAlexaboutno aff
Asha Mohamed, Steve Slade

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsDescriptive statisticsContext (archaeology)Family medicineLogistic regressionPrimary careMedicineHealth carePopulationEnvironmental healthInternal medicineGeography

Abstract

fetched live from OpenAlex

Context Family physicians (FP) provide care in many settings, including primary care clinics, hospitals, and elsewhere. Despite its health benefit, a growing number of Canadians are without a regular source of care. This portends a need to study influences on FP decisions to provide comprehensive care to a group of patients over the long term. Objective To evaluate broad factors that are associated with FP practice as comprehensive primary care providers. Study Design and Analysis Descriptive study using linked data from self-response surveys and from secondary administrative data to examine factors that are associated with FP comprehensive primary care practice. One-way crosstabulations and chi-square statistics were used to identify significant factors (p<0.05). Logistic regression was used to evaluate the relative weights of associated factors. Dataset The College of Family Physicians of Canada (CFPC) membership database and Family Medicine Longitudinal Survey (FMLS). Population Studied Family physicians who completed family medicine training in Canada in 2018-2019, and responded to the FMLS survey three years into fully licensed practice (2021-2022). Intervention/Instrument FMLS self-response, online questionnaires and administrative data created through CFPC membership. Outcome Measure FP providing comprehensive care to a group of patients over long term (Yes/No) Results Three years into fully licensed practice, 82% of FPs said they “provide comprehensive care to a current group of patients over the long term”. Those who were “proud to be an FP” at the end of residency training were more likely to provide this type of care than those who were not (84% vs 69%). FPs who do office-based clinical procedures were more likely to provide comprehensive care over the long term (90%), as were those in patient’s medical home (PMH) practices (92%). FPs who do in-hospital clinical procedures are less likely to provide comprehensive care to a group of patients (72%) as are those with certificates of added competence in emergency medicine (36%). Conclusions Several factors influence FPs likelihood of caring for a group of patients over the long term. Professional identity at the end of residency training is an important signal, as are enabling practice conditions, like the PMH model. A key finding is that while FPs contribute significantly to hospital-based care, it can impede the delivery of comprehensive, ongoing primary care to a specific patient group.

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)0.003
metaresearch head score (Gemma)0.017
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.066
GPT teacher head0.409
Teacher spread0.342 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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