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Record W2143718525 · doi:10.5430/jha.v5n1p34

Patient Centered Medical Home transformation at an academic medical center

2015· article· en· W2143718525 on OpenAlexvenueno aff
Randy Wexler, Jennifer Lehman, Mary Jo Welker

Bibliographic record

VenueJournal of Hospital Administration · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedical homeMedicineGovernment (linguistics)Family medicineCenter (category theory)Health carePrimary careNursingPolitical science

Abstract

fetched live from OpenAlex

Background: Primary care is playing an ever increasing role in the design and implementation of new models of healthcare focused on achieving policy ends as put forth by government at both the state and federal level. The Patient Centered Medical Home (PCMH) model is a leading design in this endeavor.Objective: We sought to transform family medicine offices at an academic medical center into the PCMH model of care with improvements in patient outcomes as the end result.Results: Transformation to the PCMH model of care resulted in improved rates of control of diabetes and hypertension and improved prevention measures such as smoking cessation, mammograms, Pneumovax administration, and Tdap vaccination. Readmission rates also improved using a care coordination model.Conclusions: It is possible to transform family medicine offices at academic medical centers in methods consistent with newer models of care such as the PCMH model and to improve patient outcomes. Lessons learned along the way are useful to any practice or system seeking to undertake such transformation.

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)0.006
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 score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0040.002
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0180.002

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 head0.056
GPT teacher head0.425
Teacher spread0.369 · 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
Published2015
Admission routes1
Has abstractyes

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