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Record W1967186090 · doi:10.4212/cjhp.v65i5.1173

Ascertaining Problems with Medication Histories

2012· article· en· W1967186090 on OpenAlexaffvenue
Henry Halapy, Heather Kertland

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2012
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsDocumentationFocus groupFamily medicineMedicineQualitative researchMedical recordHealth careMedication ReconciliationNursingPharmacyPharmacist

Abstract

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Background: Accurate and complete medication histories are not always obtained in clinical practice.Objective: This qualitative research study was undertaken to explore the barriers to and facilitators of obtaining accurate medication histories.Methods: Individual interviews, based on a structured interview guide, were conducted with 25 patients from both inpatient and ambulatory care clinic settings. Focus groups, based on a semistructured interview guide, were conducted with pharmacists, medical residents, and nurses. Transcribed data were analyzed by forming coded units and assessing these units for emerging themes.Results: Major themes that emerged from the patient interviews included patient ownership of health and medication knowledge (with knowledge of medications and their side effects and how to take medications being seen as important), patient-specific strategies to improve medication histories (e.g., use of regularly updated medication lists), and suggestions for system-level facilitators to improve medication histories (e.g., centralized databases of medication histories, increased patient education regarding the use and purpose of medications). Major themes also emerged from focus groups with health care professionals, including shared responsibility for medication history-taking among all 3 health care professions, perceptions about the barriers to medication history-taking (including patients not knowing their medications and not bringing their medication lists), and suggestions to improve medication histories (e.g., educating patients to bring medication vials to hospital admissions and appointments, using a centralized computer database for medication histories).Conclusions: Key recommendations resulting from this study include using standardized documentation techniques for medication histories, recording of medication history information in centralized electronic databases, educating patients to bring medications to every health care visit, and establishing criteria for pharmacist referral for cases involving complex medication histories.RÉSUMÉContexte : Les histoires médicamenteuses précises et complètes ne sont pas toujours obtenues en pratique clinique.Objectif : La présente recherche qualitative a été menée pour examiner les obstacles et les aides à l’obtention d’histoires médicamenteuses précises.Méthodes : Des entrevues individuelles structurées ont été effectuées avec 25 patients hospitalisés ou traités dans une clinique de soins ambulatoires. Des groupes de discussion, à l’aide d’un guide d’entrevue semi-structurée, ont été menés avec des pharmaciens, des médecins résidents et du personnel infirmier. Les données transcrites ont été analysées en développant des unités codées et en évaluant ces dernières à la recherche de thèmes émergents.Résultats : Les principaux thèmes ayant émergé des entrevues avec les patients étaient notamment leur responsabilité à l’égard de leur santé et leur connaissance des médicaments (la connaissance des médicaments, de leurs effets secondaires et de la façon de les prendre étant vue comme importante), les stratégies propres au patient pour améliorer les histoires médicamenteuses (p. ex., le recours à des listes de médicaments mises à jour périodiquement) et les suggestions d’aides au niveau des systèmes permettant d’améliorer les histoires médicamenteuses (p. ex., bases de données centralisées sur les histoires médicamenteuses, information accrue des patients sur l’utilisation et le but des médicaments). Des thèmes majeurs ont également émergé des groupes de discussion avec les professionnels de la santé, dont la responsabilité commune de la collecte des histoires médicamenteuses par les trois professions représentées, les perceptions des obstacles à cette collecte (notamment les patients qui ne connaissent pas les médicaments qu’ils prennent et ceux qui n’apportent pas leurs listes de médicaments) et les suggestions d’aides à l’amélioration des histoires médicamenteuses (p. ex., sensibiliser les patients sur l’importance d’apporter leurs flacons de médicaments lors d’admission ou de rendez-vous à l’hôpital, l’utilisation d’une base de données informatique centralisée sur les histoires médicamenteuses).Conclusions : Les principales recommandations issues de cette étude sont notamment de recourir à des techniques de constatation des histoires médicamenteuses standardisées, de consigner les renseignements sur les histoires médicamenteuses dans des bases de données informatiques centralisées, de sensibiliser les patients à l’importance d’apporter leurs médicaments à chaque consultation d’un professionnel de la santé et d’établir des critères pour les demandes de consultation aux pharmaciens pour les cas comportant des histoires médicamenteuses complexes.

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)0.026
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.118
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0020.004
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.103
GPT teacher head0.363
Teacher spread0.260 · 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 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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Citations13
Published2012
Admission routes2
Has abstractyes

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