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Record W1985413995 · doi:10.4212/cjhp.v63i5.947

Best Possible Medication History in the Emergency Department: Comparing Pharmacy Technicians and Pharmacists

2010· article· en· W1985413995 on OpenAlexaffvenue
Rochelle M. Johnston, Lauza Saulnier, Odette N. Gould

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2010
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMount Allison UniversityHorizon Health Network
Fundersnot available
KeywordsPharmacyEmergency departmentMedical emergencyMedicineClinical pharmacyFamily medicineEmergency medicineNursing

Abstract

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Background: Obtaining an accurate and complete medication list (i.e., the best possible medication history [BPMH]) is the first step in completing medication reconciliation. The ability of pharmacy technicians to obtain medication histories, relative to that of pharmacists, has not been formally assessed.Objectives: To determine whether pharmacy technicians at the authors' institution could obtain a BPMH as accurately and completely as pharmacists and if both groups met national norms for unintentional discrepancies and the success index for medication reconciliation.Methods: Pharmacy technicians were trained in obtaining a BPMH at the beginning of the study, before any patients were enrolled. Patients presenting to the emergency department were prospectively enrolled to be interviewed separately by both a pharmacist and a technician, with information recorded on standard medication reconciliation forms. The completed forms for each patient were compared following each set of interviews, and discrepancies were clarified with the patient.Results: Fifty-nine patients were included in the study, and 3 pharmacists and 2 technicians obtained the histories. There was no significant difference between pharmacists and technicians in terms of discrepancies involving prescription drugs (χ2 = 0.52, df = 1, n = 118, p = 0.47, Cramer's V for effect size = 0.07) or over-the-counter medications (χ2 = 0.09, df = 1, n = 118, p = 0.77, Cramer's V = 0.03). The mean number of discrepancies per patient did not differ significantly between the pharmacists and technicians (t = 0.15, df = 58, p = 0.88 for prescription drugs; t = -0.22, df = 58, p = 0.83 for over-the-counter products). For both groups, the number of unintentional discrepancies per patient was significantly lower and the success index for medication reconciliation significantly higher than the national average.Conclusions: Trained pharmacy technicians at the authors' institution were able to obtain a BPMH with as much accuracy and completeness as pharmacists. Both groups were significantly superior to the national average in terms of unintentional discrepancies and success index for medication reconciliation.RÉSUMÉContexte : L'obtention d'une liste précise et complète des medicaments (c.-à-d. le meilleur schéma thérapeutique possible [MSTP]) est la première étape du bilan comparatif des médicaments. La capacité des techniciens en pharmacie, comparativement à celle des pharmaciens, d'obtenir les histoires médicamenteuses n'a pas été évaluée officiellement.Objectifs : Déterminer si les techniciens en pharmacie dans l'établissement des auteurs pouvaient obtenir un MSTP aussi précis et complet que les pharmaciens et si les deux groupes satisfaisaient aux normes nationals pour ce qui est des divergences non intentionnelles et de l'indice de réussite pour ce qui est du bilan comparatif des médicaments.Méthodes : Les techniciens en pharmacie ont été formés sur la technique d'obtention du MSTP au début de l'étude, avant l'inscription des patients. Les patients qui consultaient au service des urgences ont été inscrits de façon prospective pour être interviewés séparément par un pharmacien et par un technicien, et l'information était consignee sur des formulaires standard de bilan comparatif des médicaments. Les formulaires remplis pour chaque patient ont été comparés à la suite de chaque série d'entrevues, et les divergences ont été clarifiées avec les patients.Résultats : Un total de 59 patients ont été inscrits à l'étude. Trois pharmaciens et deux techniciens ont obtenu les histoires médicamenteuses. Aucune différence significative n'a été observée entre les pharmaciens et les techniciens pour ce qui est des divergences au chapitre des medicaments d'ordonnance χ2 = 0,52, df = 1, n = 118, p = 0,47, V de Cramer pour l'ampleur de l'effet = 0,07) ou des médicaments en vente libre (χ2 = 0,09, df = 1, n = 118, p = 0,77, V de Cramer = 0,03). Aucune difference significative n'a été observée quant au nombre moyen de divergences par patient entre les pharmaciens et les techniciens (t = 0,15, df = 58, p = 0,88 pour les médicaments d'ordonnance; t = - 0,22, df = 58, p = 0,83 pour les produits en vente libre). Le nombre de divergences non intentionnelles par patient pour les deux groupes était significativement plus bas et l'indice de réussite pour ce qui est du bilan comparatif des medicaments était significativement plus élevé que les moyennes nationales.Conclusions : Les techniciens en pharmacie qualifiés dans l'établissement des auteurs ont pu obtenir un MSTP aussi précis et complet que celui des pharmaciens. Les deux groupes ont eu des résultats significativement supérieurs à ceux de la moyenne nationale quant aux divergences non intentionnelles et à l'indice de réussite pour ce qui est du bilan comparative des médicaments.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.872
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.104
GPT teacher head0.382
Teacher spread0.279 · 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.

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".

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Citations101
Published2010
Admission routes2
Has abstractyes

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