Determining the optimal threshold for medication adherence in adult asthma patients: an analysis of British Columbia administrative health database in Canada
Bibliographic record
Abstract
This study investigated the association between varying cutoffs for Medication Adherence (MA) among physician-diagnosed asthma patients and subsequent association with asthma exacerbation. We linked four administrative health databases obtained from the Population Data in British Columbia. Index cases were physician-diagnosed asthma patients between January 1, 1998, to December 31, 1999, aged 18 years and older. Patients were prospectively assessed in the follow-up period from January 1, 2000, to December 31, 2018, to identify asthma exacerbation. Two proxy measures were used to assess MA: the proportion of days covered (PDC) and the medication possession ratio (MPR). Using the generalized estimating equation (GEE) logistic regression adjusted for patient covariates, the outcome of “asthma exacerbation” was modeled against varying MA cutoffs; excellent ‘≥0.90’; very good ‘0.80–0.89’; good ‘0.70–0.799’; moderate ‘0.6–0.699’; mild ‘0.50–0.599’ compared to poor ‘<0.50’ for both PDC and MPR. The sample included 68,211 physician-diagnosed asthma patients with a mean age of 48.2 years and 59.3% females. The adjusted odds ratios (OR) and 95% confidence interval (CI) at the various cutoff for PDC-levels predicting asthma exacerbation events were: Excellent MA [OR = 0.84, 95% (0.82–0.86), very good MA [OR: 0.86, (0.83, 0.89), good MA [0.91, (0.88–0.94)]; moderate MA [0.93, (0.90–0.96)]; mild MA [0.95, (0.92–0.98)]; compared to poor MA level. Threshold levels for both the PDC and MPR measure greater than 0.80 provided optimal threshold associated with over 15% reduced likelihood of experiencing asthma exacerbations. Intervention aimed at improving asthma exacerbation events in adult asthma patients should encourage increased medication adherence threshold level greater than 0.80. Supplemental data for this article is available online at at www.tandfonline.com/ijas .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".