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Development of clinical indicators for type 2 diabetes

2008· article· en· W2024937860 on OpenAlexaffvenueabout
Neil J. MacKinnon, Nicole R. Hartnell, Emily Black, Peggy Dunbar, Jeffrey Johnson, Susan Halliday-Mahar, Rumi Pattar, Ehud Ur

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2008
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHealth Sciences CentreUniversity of British ColumbiaUniversity of AlbertaDalhousie University
Fundersnot available
KeywordsMedicineDelphi methodType 2 diabetesNova scotiaFamily medicineDiabetes mellitusHealth carePharmacyDelphi

Abstract

fetched live from OpenAlex

Background/Objective:Preventable drug-related morbidity in patients with type 2 diabetes is a major concern. Our objective was to develop a set of Canadian clinical indicators of preventable drug-related morbidity (PDRM) and preventable care-related morbidity (PCRM) for type 2 diabetes.Methods:Each study partner (Dalhousie University, Nova Scotia Department of Health, Diabetes Care Program of Nova Scotia, and Sobeys Pharmacy Group) was asked to identify the priorities of medication-related diabetes care from the Canadian Diabetes Association 2003 clinical practice guidelines using the nominal group technique. Based on the priorities identified, a survey was constructed listing the clinical outcome and pattern of care related to a number of possible PDRMs/PCRMs in patients with type 2 diabetes. Using the Delphi technique, an interdisciplinary panel of 10 experts scored each clinical indicator in an attempt to achieve consensus.Results:Education/reinforcement of targets was identified by the nominal group t...

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)0.002
metaresearch head score (Gemma)0.004
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 score0.708
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.415
GPT teacher head0.494
Teacher spread0.079 · 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 designNot applicable
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

Citations7
Published2008
Admission routes3
Has abstractyes

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