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Record W2188243274 · doi:10.1370/afm.815

Narrative Reports to Monitor and Evaluate the Integration of Pharmacists Into Family Practice Settings

2008· article· en· W2188243274 on OpenAlexaff
Kevin Pottie, Susan Haydt, Barbara Farrell, C. Paul Sellors, William Hogg

Bibliographic record

VenueThe Annals of Family Medicine · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMcMaster UniversityUniversity of OttawaStem Cell NetworkUniversity of TorontoInstitute of Population and Public HealthBruyèreÉlisabeth Bruyère Hospital
Fundersnot available
KeywordsMedicineNarrativeMedical educationNarrative reviewNursingFamily medicineIntensive care medicine

Abstract

fetched live from OpenAlex

PURPOSE: Narratives can capture unfolding events and negotiation of roles and thus can help to evaluate interventions in interdisciplinary health care teams. We describe a practical qualitative method, the narrative report, and its role in evaluating implementation research. METHODS: We used narrative reports as a means to evaluate an intervention to integrate pharmacists into group family practices. The pharmacists submitted 63 written narrative reports during a 1-year period. Our interdisciplinary research team analyzed these reports to monitor the progress of the implementation, to identify pharmacists' needs, and to capture elements of the integration process. RESULTS: The monthly narrative reports allowed the research team to document early learning and calibrate the program in terms of clinical support, adapting roles, and realigning expectations. The reports helped the research team stay in tune with practice-related implementation challenges, and the preliminary summary of narrative findings provided a forum for sharing innovations among the integrating pharmacists. CONCLUSION: The narrative report can be a successful qualitative tool to track and evaluate the early stages of an intervention in the context of evolving primary health care teams.

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)0.012
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.822
GPT teacher head0.727
Teacher spread0.094 · 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 designQualitative
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

Citations16
Published2008
Admission routes1
Has abstractyes

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