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Record W4388307155 · doi:10.1177/23743735231211782

Patient Experience With Primary Care Physician Assistants in Ontario, Canada: Impact of Trust, Knowledge, and Access to Care

2023· article· en· W4388307155 on OpenAlexaffabout
Kristen Burrows

Bibliographic record

VenueJournal of Patient Experience · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPrimary carePhysician assistantsFamily medicineMedicineNursingScope of practiceMedical homePrimary care physicianPatient careHealth careNurse practitioners

Abstract

fetched live from OpenAlex

Physician assistants (PAs) have been integrated into primary care settings to reduce wait times and to optimize continuity of care. Though previous studies suggest that PA utilization leads to improved healthcare access, few studies have investigated patient experience with primary care PAs in Canada. The objective of this study is to explore patient perspectives on primary care PAs in Ontario. A patient survey was developed and distributed to patients seen by PAs in 4 family medicine practices across Ontario, Canada. Results demonstrate that many patients are highly satisfied with their experience including the PA's ability to address their medical needs, establish rapport, and provide fast access to care (including same-day and after-hours appointments). Despite preferring to see a physician for more complex concerns, participants felt that PAs demonstrate similar medical knowledge, competencies, and scope of practice as family physicians. Patients demonstrated a solid understanding of the PA role and recognized the collaborative PA-physician relationship. These findings describe successful patient awareness and acceptance of the PA profession, largely due to positive PA-patient interactions in family medicine settings.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.404
Teacher spread0.364 · 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 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
Published2023
Admission routes2
Has abstractyes

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