Frequency and predictors of tablet splitting in statin prescriptions: a population-based analysis.
Bibliographic record
Abstract
BACKGROUND: The price per milligram for most statin medications decreases at higher strengths, which provides an economic incentive to split tablets. We sought to determine the frequency with which statin tablets are split, and to evaluate factors associated with this practice. METHODS: We obtained prescription claims data for statins from the BC Ministry of Health for the period Jan. 1, 1996, to Dec. 31, 2006. We estimated the number of tablets per day, based on the ratio of the number of tablets to days-supply in each prescription, to estimate the frequency with which splitting occurred with each statin. We used multivariable logistic regression to assess patient and physician characteristics and the level of public drug plan coverage associated with tablet splitting. To estimate related cost savings, we used information on drug costs and quantities of dispensed statins reported by pharmacies. RESULTS: During the 11-year study period, we estimated that tablet splitting occurred in 2.6% of 7.2 million statin prescriptions. There was an increasing trend in the practice over time, to 4.5% of prescriptions in 2006. Lovastatin was the only scored tablet and was the most likely to be split, followed by rosuvastatin and atorvastatin. Fifty percent of the prescriptions in which tablet splitting occurred were prescribed by only 7.9% of the routine statin prescribers (i.e., > 10 statin prescriptions over the study period). Specialists were less likely than general practitioners to prescribe statins that were subsequently split (odds ratio [OR] 0.43, 95% confidence interval [CI] 0.40-0.46). Statin prescriptions that were fully covered by the public drug plan were half as likely as those with no such coverage to involve tablet splitting (OR 0.48, 95% CI 0.44-0.92). Having no public drug coverage, having a low annual household income and being female were patient factors found to be positively associated with tablet splitting. In 2006, the cost savings associated with tablet splitting was $2.3 million. INTERPRETATION: The frequency of tablet splitting in statin prescriptions in British Columbia was low but increased over time. It varied between patients, physicians and different levels of insurance coverage. In the final study year, 94.5% of the statin prescriptions were dispensed at strengths for which a tablet of twice the strength was available and could have been split, which suggests a potentially enormous cost savings.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".