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Record W2136365330 · doi:10.18553/jmcp.2002.8.5.372

Preventable Drug-related Morbidity Indicators in the U.S. and U.K.

2002· article· en· W2136365330 on OpenAlexfundno aff
Caroline Morris, Judy Cantrill

Bibliographic record

VenueJournal of Managed Care Pharmacy · 2002
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
FundersFaculty of Medicine, Dalhousie UniversityDalhousie University
KeywordsDelphi methodMedicineViewpointsRelevance (law)Health careQuality (philosophy)DelphiSample (material)PharmacyFamily medicineStatisticsPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To qualitatively describe differences between a series of preventable drug-related morbidity (PDRM) indicators in the United States (U.S.) and the United Kingdom (U.K.), after transfer from the U.S. to the U.K. health care setting. METHODS: A preliminary validation was undertaken of the U.S.-derived indicators within the University of Manchester School of Pharmacy, followed by a 2-round Delphi questionnaire of a sample of general practitioners (n=6) and primary care pharmacists (n=10). The main outcome measures were (1) relevance of the U.S. indicators to U.K. primary care prescribing as determined by preliminary validation and (2) the establishment of consensus among the Delphi participants that an indicator represented PDRM. RESULTS: After preliminary validation, 7 of the U.S. indicators and a part of 2 indicators were considered of insufficient relevance to take any further part in the validation process. A further 18 of the U.S.-derived indicators failed to achieve consensus as PDRMs by the U.K. Delphi panel. At the end of the validation process, 19 indicators remained. CONCLUSIONS: Many of the U.S.-derived indicators lacked relevance in the U.K. due to differences in transatlantic clinical practice. In addition, there may be differences in the philosophical viewpoints of health professionals practising in the U.S. and the U.K. In practice, it is therefore inappropriate to transfer quality indicators of this nature directly from the U.S. to the U.K. However, if some form of validation process is undertaken, indicators derived in one health care setting appear to provide a very useful starting point for those developed in another.

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 score0.738
Threshold uncertainty score0.508

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)0.0000.000

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 head0.096
GPT teacher head0.387
Teacher spread0.291 · 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".

Quick stats

Citations13
Published2002
Admission routes1
Has abstractyes

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