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6ER-031 Roles and impacts of the pharmacist from 1990 to the present: literature review and research perspective

2018· article· en· W2804507419 on OpenAlexaffabout
É. Ferrand, Denis Lebel, Maxime Bergeron, JF Bussières

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPerspective (graphical)PharmacistMedicineMedical educationEngineering ethicsPsychologyNursingComputer sciencePharmacyEngineering

Abstract

fetched live from OpenAlex

Background There are an increasing number of publications concerning the roles and impacts of pharmacists. Decision makers, clinicians and patients need evidence to support an appropriate allocation of funds to better use the expertise of pharmacists. Purpose To provide a profile of the roles and impacts of the pharmacist in the literature. Material and methods Review of literature. Articles in English and French related to the roles and the impacts of the pharmacist were selected, according a reproducible search strategy from 1990 to September 2017 in Pubmed and Pubmed Central. The following variables were extracted: author, country, study plan, pharmaceutical activities, patient care programmes, diseases, outcomes (e.g. mortality, morbidity, costs, adverse events, medication errors, compliance, satisfaction, other) and a quality score. Outcome results were categorised as positive, neutral or negative. Only descriptive statistics were performed. Results On 20 September, 2017, a total of 2323 articles were included on 100 themes (e.g. 41 pharmaceutical activities, 30 diseases and 29 patient care programmes). Studies were conducted in the United States (46.6%), multiple countries (8.2%), Canada (7.8%), France (6.2%), the United Kingdom (5.3%), Australia (3.6%) and other countries (19.3%). Studies were either cross-sectional (47%), retrospective (33%), prospective (18%) or uncategorised (12%). Outcomes included morbidity (22%), medication errors (11.7%), satisfaction (7.3%), adherence (6%), costs (5.6%), adverse reactions (3.7%), mortality (1.3%) and others (42.4%). Included studies reported 6784 descriptive indicators and 5108 outcome indicators (60% were positive, 39% neutral and 1% negative). The quality score of articles (n=1,697) were either excellent (8.8%), acceptable (34.2%) or with methodological limitations (57%). Conclusion This review of the literature confirms the extensive presence of pharmacists in numerous patient care programmes, treating different diseases and performing a variety of pharmaceutical activities. Most outcomes related to pharmaceutical activities were positive. However, a significant proportion of published studies had methodological limitations. Pharmacists need to be more exposed to evidence about their roles and their impact, both in community and hospital settings. Furthermore, increasing funding for evaluative research must be supported by external stakeholders in different countries to better understand the impact of pharmacists’ activities. No conflict of interest

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)0.017
metaresearch head score (Gemma)0.044
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0230.018
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0020.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.176
GPT teacher head0.514
Teacher spread0.339 · 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
GenreReview

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
Published2018
Admission routes2
Has abstractyes

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