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Record W2462436320 · doi:10.3122/jabfm.2016.s1.160017

Patient Relationships and the Personal Physician in Tomorrow's Health System: A Perspective from the Keystone IV Conference

2016· article· en· W2462436320 on OpenAlexaffabout
Jack M. Colwill, John Frey, M. A. Baird, John W. Kirk, W W Rosser

Bibliographic record

VenueThe Journal of the American Board of Family Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineReimbursementPerspective (graphical)WorkforceAccountabilityNursingHealth careValue (mathematics)Medical educationHealth care reformFamily medicineHealth policyPublic health

Abstract

fetched live from OpenAlex

A group of senior leaders from the early generation of academic family medicine reflect on the meaning of being a personal physician, based on their own clinical experiences and as teachers of residents and students in academic health centers. Recognizing that changes in clinical care and education at national and local systems levels have added extraordinary demands to the role of the personal physician, the senior group offers examples of how the discipline might go forward in changing times. Differently organized care such as the Family Health Team model in Ontario, Canada; value-based payment for populations in large health systems; and federal changes in reimbursement for populations can have positive effects on physician satisfaction. These changes and examples of changes in medical student and residency education also have the potential to positively affect the primary care workforce. The authors conclude that, without substantive educational and health system reform, the ability to truly serve as a personal physician and adhere to the values of continuity, responsibility, and accountability will continue to be threatened.

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)0.006
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.037
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0270.012
Scholarly communication0.0110.007
Open science0.0020.006
Research integrity0.0080.017
Insufficient payload (model declined to judge)0.0090.001

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 head0.075
GPT teacher head0.385
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations12
Published2016
Admission routes2
Has abstractyes

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