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Record W1957215797 · doi:10.1185/03007995.2015.1077213

Pharmacy quality alliance measure: adherence to non-warfarin oral anticoagulant medications

2015· article· en· W1957215797 on OpenAlex
Concetta Crivera, Winnie W. Nelson, Brahim Bookhart, Silas Martin, Guillaume Germain, François Laliberté, Jeffrey Schein, Patrick Lefèbvre

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

VenueCurrent Medical Research and Opinion · 2015
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsDabigatranRivaroxabanApixabanMedicineWarfarinMedicare Part DLogistic regressionInternal medicinePharmacyAtrial fibrillationMedical prescriptionPharmacologyFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Pharmacy Quality Alliance (PQA) recently endorsed adherence to non-warfarin anticoagulant agents as a new performance measure, but the Medicare Part D Star Ratings program has not yet adopted the measure. The current study aims to assess the real-world adherence to medication of patients who used non-vitamin-K-antagonist oral anticoagulants (NOACs) based on the PQA's adherence measure. METHODS: Healthcare claims from the Humana database during the year of 2013 were analyzed. Patients older than 18 with ≥2 dispensings of NOAC agents, at least 180 days apart between two NOAC dispensings in 2013 (a criterion to include chronic users), with ≥60 days of supply, and ≥180 days of continuous enrollment prior to the index NOAC were identified. The PQA measure on the index therapy was calculated as the percentage of patients who had a proportion of days covered (PDC) ≥0.8 during their follow-up. RESULTS: A total of 9948 NOAC users (rivaroxaban: n = 4194, dabigatran: n = 5489, apixaban: n = 265) were identified. For rivaroxaban users, the proportion of patients with a PDC ≥0.8 (PQA measure) at 75.4% was significantly higher compared to dabigatran users (67.6%; P < 0.001) and higher compared to apixaban users (70.6%; P = 0.076). When allowing switches to other NOAC agents in the PQA measure, rivaroxaban users had a significantly higher PQA measure at 76.9% compared to both dabigatran (72.9%; P < 0.001) and apixaban (71.3%; P = 0.037) users. Multivariate logistic regression analyses corroborated the findings that rivaroxaban had a significantly higher adherence compared to the other NOAC agents. LIMITATIONS: Claims data may have contained inaccuracies, possible change in patterns over time, and the impossibility of knowing whether all supplied tablets were taken. CONCLUSION: Based on the PQA's adherence measure, rivaroxaban users were found to have a higher adherence compared to dabigatran and apixaban users. Healthcare providers may want to consider the impact of anticoagulation selection on their ability to achieve quality metrics.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
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)0.0010.002

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 head0.629
GPT teacher head0.599
Teacher spread0.030 · 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