Patterns of Antipsychotic Dispensation to Long-Term Care Residents
Bibliographic record
Abstract
OBJECTIVES: To describe dispensing patterns of antipsychotic medications to long-term care (LTC) residents and assess factors associated with continuation of an antipsychotic after a fall-related hospitalization. DESIGN: A retrospective cohort study. SETTING AND PARTICIPANTS: Nova Scotia Seniors Pharmacare Program (NSSPP) beneficiaries age 66 years and older who resided in LTC and received at least 1 dispensation of an antipsychotic within the study period of April 1, 2009, to March 31, 2017. METHODS: Linkage of administrative claims data from the NSSPP and the Canadian Institute of Health Information Discharge Abstract Database identified LTC residents with an antipsychotic dispensation and from the subgroup of those dispensed antipsychotic medications who experienced a fall-related hospitalization. Antipsychotic dispensing patterns were reported with counts and means. Predictors of continuation of an antipsychotic after a fall-related hospitalization (sex, length of stay, days supplied, age, year of admission, rural/urban) were reported and analyzed with multiple logistic regression. RESULTS: There were 19,164 unique NSSPP beneficiaries who were dispensed at least 1 prescription for an antipsychotic medication. Of those who received at least 1 antipsychotic dispensation 90% (n = 17,201) resided in LTC. A mean of 40% (n = 2637) of LTC residents received at least 1 antipsychotic dispensation in each year. Risperidone and quetiapine were dispensed most frequently. Of the 544 beneficiaries residing in LTC who survived a fall-related hospitalization, 439 (80.7%) continued an antipsychotic after hospital discharge. Female sex [OR 1.7, 95% CI (1.013‒2.943)], age 66‒69 [OR 4.587, 95% CI (1.4‒20.8)], 75-79 [OR 2.8, 95% CI (1.3‒6.3)], and 80‒84 years [OR 3.1, 95% CI (1.6‒6.4)] (compared with age 90+ years) were associated with increased risk of antipsychotic continuation. CONCLUSIONS AND IMPLICATIONS: With 90% of antipsychotic dispensations in Nova Scotia being to LTC residents and 40% of LTC residents being dispensed antipsychotics in any year there is a need to address this level of antipsychotic dispensation to older adults.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".