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Record W4375951557 · doi:10.17480/psk.2023.67.2.118

Current Status of Comprehensive Medication Management in Long-term Care Facilities: Focused on Australia, Canada, the United Kingdom and the United States

2023· article· en· W4375951557 on OpenAlex
Hyunji Cho, Tae Hyun Kim, Suhyun Jang, Hee-Jin Kang, Ju‐Yeun Lee, Eun-Young Bae, Joo‐Hyun Lee, Young‐Mi Ah, Hyekyung Park, Sunmee Jang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueYakhak Hoeji · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacy and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolypharmacyLong-term careService (business)MedicineBusinessNursingMarketing

Abstract

fetched live from OpenAlex

Polypharmacy and potentially inappropriate medication use have increased among the residents of long-term care facilities (LTCF). Nevertheless, Comprehensive Medication Management (CMM) for LTCF residents was not implemented in Korea. The United Kingdom, Canada, the United States, and Australia have already introduced CMM for managing drug-related problems in LTCF. This study discussed the implications of developing the CMM service for LTCF residents in Korea by reviewing the system of these countries. The contents and requirements of CMM are investigated through relevant papers and official reports of the public institution of each country. The CMM service of these countries is regularly conducted based on their system and laws. In Canada, there are no additional requirements such as special education and qualifications for pharmacists providing CMM. But in other countries, it is preferred that pharmacists providing CMM are geriatric pharmacists or take the education that is equivalent to them. In addition, all these countries utilize national computer networks or electronic healthcare records that are used for executing CMM and for sharing with other medical experts, and then they are retained as official medical records. It is necessary to consider the system of other countries when introducing the CMM service for LTCF residents in Korea.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.224
GPT teacher head0.475
Teacher spread0.251 · 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