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Record W2147142421 · doi:10.4212/cjhp.v64i2.994

Toward a Unified Model for Contemporary Institutional Pharmacy Practice

2011· article· en· W2147142421 on OpenAlexvenueaboutno aff
James E. Tisdale

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2011
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacyPharmacy practiceFamily medicineMedicine

Abstract

fetched live from OpenAlex

TisdaleW hen a patient sees a physician anywhere in Canada or the United States, chances are high that the approach the physician takes to assessing and diagnosing actual or potential medical problems will be virtually the same as that of other physicians, regardless of geographic location or practice setting.Although different physicians may arrive at different diagnoses or different treatment plans for the same diagnosis, the process that they use to reach those decisions is consistent and essentially universal.This congruence reflects the fact that physicians have an established, consistent, widely accepted practice model.The same is true for dentists, as well as for the vast majority of other health care professionals.On the other hand, when a patient is under the care of a hospital pharmacist in Canada or the United States, it is likely that the pharmacist's approach to assessing and diagnosing drug therapy problems will not be the same as and, in many cases, will not be remotely similar to that of other hospital pharmacists.The approaches of institutional pharmacists to the assessment and diagnosis of drug therapy problems and to the development of treatment plans vary widely from practitioner to practitioner, from institution to institution, and even from patient care unit to patient care unit within the same institution.Furthermore, chances are that the specific role of the pharmacist on the health care team will vary from institution to institution and from unit to unit.More broadly, specific drug distribution models, and the overall process of ensuring that the right patient receives the right drug at the right time, also vary widely from institution to institution, as do the roles assigned to pharmacy technicians.Even the technologies that we use in our drug distribution systems vary substantially from institution to institution.1,2 In brief, the profession of pharmacy, including pharmacy as practised in institutional settings, does not have an established, consistent, widely accepted practice model.Why is this so?Why don't pharmacists have an established, consistent, widely accepted practice model?Part of the reason may be that the role of pharmacists within the health care system has not been precisely defined.I would propose that the role of the pharmacist, as an integral and indispensable member of collaborative multidisciplinary health care teams, is to identify, diagnose, and manage (or prevent) actual and potential drug

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)0.053
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.296

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.005
Science and technology studies0.0120.050
Scholarly communication0.0420.033
Open science0.0070.017
Research integrity0.0130.017
Insufficient payload (model declined to judge)0.0050.002

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 head0.381
GPT teacher head0.415
Teacher spread0.034 · 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 designTheoretical or conceptual
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
Published2011
Admission routes2
Has abstractyes

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