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Record W4225085559 · doi:10.1136/bmjhci-2021-100540

‘Improving smart medication management’: an online expert discussion

2022· review· en· W4225085559 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ Health & Care Informatics · 2022
Typereview
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsMcGill University
FundersBD
KeywordsSAFERPatient safetyMedicineHealth careQuality (philosophy)Electronic prescribingMedical emergencyNursingMedical educationComputer sciencePharmacyPolitical scienceComputer security

Abstract

fetched live from OpenAlex

Medication safety continues to be a problem inside and outside the hospital, partly because new smart technologies can cause new drug-related challenges to prescribers and patients. Better integrated digital and information technology (IT) systems, improved education on prescribing for prescribers and greater patient-centred care that empowers patients to take control of their medications are all vital to safer and more effective prescribing. In July 2021, a roundtable discussion was held as a spin-off meeting of the International Forum on Quality and Safety in Health Care Europe 2021 to discuss challenges and future direction in smart medication management. This manuscript summarises the discussion focusing on the aspects of digital and IT systems, safe prescribing, improved communication and education, and drug adherence.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.179
GPT teacher head0.469
Teacher spread0.290 · 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