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Record W7064081475

Anti-Hyperglycemic Medication Adherence and Health Services Utilization in People with Diabetes: A Longitudinal Study of Alberta’s Tomorrow Project

2022· other· en· W7064081475 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.

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

VenueDove Medical Press (Taylor and Francis Group) · 2022
Typeother
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsLongitudinal studyPublic healthHealth careMedication adherenceGeneralized estimating equationCohort studyCohortDiabetes mellitus
DOInot available

Abstract

fetched live from OpenAlex

Ming Ye,1 Jennifer E Vena,2 Jeffrey A Johnson,1 Grace Shen-Tu,2 Dean T Eurich1 1School of Public Health, University of Alberta, Edmonton, Alberta, Canada; 2Alberta’s Tomorrow Project, CancerCare Alberta, Alberta Health Services, Calgary, Alberta, CanadaCorrespondence: Dean T Eurich, School of Public Health, University of Alberta, Canada, Email deurich@ualberta.caBackground: Little is known about the long-term (> 2 years) relationship between the time-varying drug adherence and healthcare utilization for patients with diabetes.Objective: To characterize the relationship between time-varying anti-hyperglycemic medication adherence and healthcare utilization in patients with diabetes, using data from Alberta’s Tomorrow Project, a population-based cohort study in Alberta, Canada.Methods: Incident cases of diabetes with at least 24 months of follow-up were included in the study. Anti-hyperglycemic drug adherence was measured by proportion of days covered (PDC) in the past 12 months for each year after diagnosis. The rate of healthcare utilization was assessed for the subsequent 12 months, 36 months and 60 months. A time-varying, negative binomial generalized estimating equation model was used to examine the association between medication adherence and healthcare utilization.Results: Among 2155 incident cases of diabetes, average age at diagnosis was 59.6± 9.3, 51.0% were female and average duration of follow-up was 7.3± 3.7 (range, 2.0– 16.2) years. The proportion of patients taking anti-hyperglycemic medications was 47.6% during the first year of diagnosis, which increased to 77.3% by the end of follow-up. Compared to adherent patients (PDC≥ 0.8), non-adherent patients (PDC< 0.8) had substantially higher rate of all-cause hospitalization [incident rate ratio, IRR=1.48 (1.22– 1.79), ED visits [1.30 (1.15– 1.47)] and GP visits [1.17 (1.08– 1.27)] in the subsequent 12 months. However, these associations became weaker with longer follow-up [eg, IRR=1.18 (0.98– 1.39) and 1.05 (0.94– 1.18) for all-cause hospitalization in the subsequent 36 and 60 months, respectively].Conclusion: Poor adherence among diabetic patients was associated with substantially higher rate of healthcare utilization in the short term (eg, 12 months); however, this association weakened over a longer period (eg, 36– 60 months).Keywords: diabetes, anti-hyperglycemia, adherence, time-varying, healthcare, longitudinal

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)0.000
metaresearch head score (Gemma)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.300
Teacher spread0.263 · 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