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Record W4401680821 · doi:10.1111/bcp.16216

Promoting medication safety for older adults upon hospital discharge: Guiding principles for a medication discharge plan

2024· article· en· W4401680821 on OpenAlexafffund
Fang Zhang, Justine Lauzon, Jérémy Payette, Fanny Courtemanche, Louise Papillon‐Ferland, Faranak Firoozi, Suzanne Gilbert, Justin P. Turner, Yannick Villeneuve

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2024
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-MontréalInstitut Universitaire de Gériatrie de MontréalUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital Maisonneuve-Rosemont
FundersUniversité de Montréal
KeywordsMedicineStandardizationDelphi methodPatient safetyPrioritizationPolypharmacyPlan (archaeology)MEDLINETransmission (telecommunications)Medical emergencyHealth careIntensive care medicineComputer scienceProcess management

Abstract

fetched live from OpenAlex

Older adults are at risk of adverse drug events during transition of care from hospital to community, thus optimal communication about medications at discharge is essential. Standardization of medication discharge plan (MDP) is lacking. This study aimed to (1) create a standardized MDP for older adults using consensus-based principles, (2) create a short-version MDP and (3) generate a practical guide. Modified Delphi was used to establish consensus on guiding principles for the MDP. Additionally, participants were asked about guiding principles deemed most essential, patient prioritization, the format and mode of transmission of the MDP. Twenty-six guiding principles reached consensus, with 17 prioritized for a short-version MDP. The practical guide includes explanations of the guiding principles, criteria for patient selection and recommendations on the format and mode of transmission. The results of this study will assist implementation of MDPs when older adults are discharged from hospital.

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)0.091
metaresearch head score (Gemma)0.074
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.091
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0040.002
Scholarly communication0.0030.004
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0010.001

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 head0.153
GPT teacher head0.480
Teacher spread0.327 · 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
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

Citations2
Published2024
Admission routes2
Has abstractyes

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