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Record W2117550090 · doi:10.1345/aph.1q804

Ontario Pharmacists Practicing in Family Health Teams and the Patient-Centered Medical Home

2012· article· en· W2117550090 on OpenAlexaffabout
Lisa Dolovich

Bibliographic record

VenueAnnals of Pharmacotherapy · 2012
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedical homeMedicinePharmacistPharmacyNursingFamily medicineHealth careClinical pharmacyCluster randomised controlled trialBest practicePrimary carePsychological intervention

Abstract

fetched live from OpenAlex

The patient-centered medical home (PCMH) approach continues to gather momentum in the United States and Canada as a broad approach to reform the delivery of the complete primary care system. The family health team (FHT) model implemented in Ontario, Canada, best mirrors the PCMH approach of the United States. The integration of pharmacists as key members of the health care team providing on-site, in-office coordinated care to FHT patients was included from the start of planning the FHT model and represents a substantial opportunity for pharmacists to realize their professional vision. Several research projects in Canada and elsewhere have contributed to providing evidence to support the integration of pharmacists into primary care practice sites. Two major research programs, the Seniors Medication Assessment Research Trial (SMART) cluster randomized controlled trial and the Integrating Family Medicine and Pharmacy to Advance Primary Care Therapeutics (IMPACT) multipronged demonstration project made substantial contributions to evidence-informed policy decisions supporting the integration of pharmacists into FHTs. These projects can provide useful information to support the integration of pharmacists into the PCMH and to encourage further research to better measure the effect of the pharmacist from the holistic patient-centered perspective.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.203
GPT teacher head0.479
Teacher spread0.276 · 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.

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

Citations48
Published2012
Admission routes2
Has abstractyes

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