The Variation of Statin Use Among Nursing Home Residents and Physicians: A Cross‐Sectional Analysis
Bibliographic record
Abstract
OBJECTIVES: To examine the variability of statin use among nursing home residents and prescribing physicians, and to assess statin use by resident frailty. DESIGN: Population-based, cross-sectional analysis. SETTING: All nursing home facilities (N = 631) in Ontario, Canada between April 1, 2013 and March 31, 2014. PARTICIPANTS: All adults aged 66 years and older who received a full clinical assessment while residing in a nursing home facility and their assigned, most responsible, physician. MEASUREMENTS: Statin use on date of clinical assessment. Resident- and physician-level characteristics ascertained through clinical assessment and health administrative data. Resident frailty was derived using a previously validated index. RESULTS: Among 76,226 nursing home residents assigned to 1,919 physicians, 25,648 (33.6%) were statin users. There were 13,331 (30.1%) statin users among the 44,290 residents categorized as frail. In an adjusted mixed-effects logistic regression model, frail residents (adjusted odds ratio = 0.62, 95% confidence interval 0.58-0.65) were significantly less likely to be statin users compared with non-frail residents. After adjustment for resident characteristics, the intraclass correlation coefficient indicated that between-physician variability accounted for 9.1% of the residual unexplained variation in statin use (P < .001). Among the 894 physicians assigned 20 or more residents, funnel plots confirmed there were more low-outlying (17.4%) and high-outlying (12.0%) prescribers of statins than expected by chance. Physicians who were high-outlying prescribers had higher historical rates of statin prescribing. CONCLUSIONS AND RELEVANCE: Statin prescribing was substantial within nursing homes, even among frail residents. After controlling for resident characteristics, the likelihood of statin prescribing varied significantly across physicians. Further studies are required to evaluate the risks and benefits of statin use, and discontinuation, among nursing home residents to better inform clinical practice in this setting.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".