Prescribing cascades in persons with Alzheimer’s disease: engaging patients, caregivers, and providers in a qualitative evaluation of print educational materials
Bibliographic record
Abstract
INTRODUCTION: Prescribing cascades occur when the side effect of a drug is misinterpreted as a new medical condition, and a second drug is prescribed to address the side effect. Persons with Alzheimer's disease (AD) are at increased risk of prescribing cascades due to greater multimorbidity, polypharmacy, and complexity of care. The objective of this study was to evaluate educational materials about prescribing cascades in persons with AD, and elicit input on their use in a future trial. METHODS: = 15). We coded interview transcripts and organized themes according to the communication-human information processing model. We revised the materials based on the interviews, and surveyed participating caregivers and providers for their reactions to the revised materials. RESULTS: Analysis of patients', caregivers', and providers' comments suggest: (a) Providers had conflicting views about the messaging of materials; (b) Caregivers were likely to read letters addressed to patients; (c) Providers were likely to ignore letters, but were receptive to patient/caregiver-initiated conversations; (d) Patients and caregivers had difficulty understanding prescribing cascades; (e) Providers worried that mailed materials would undermine trust; (f) Participants had mixed views on how materials might affect the clinical encounter; (g) Participants felt that materials would improve patient/caregiver engagement. When surveyed, most providers found the revised materials informative and actionable, and most caregivers found them understandable and useful. CONCLUSIONS: This evaluation of educational materials about prescribing cascades in patients with AD provides strong support for engaging caregivers to communicate with providers about prescribing cascades. By giving patients and caregivers a basic description of the prescribing cascade concept, our educational materials may help them prepare for a conversation with the provider, who can then tailor the discussion of the possible cascade to the specific needs of the individual patient and caregiver. However, evidence on whether materials can stimulate such conversations awaits testing in a future trial. LAY SUMMARY: Prescribing cascades occur when the side effect of a medication is misinterpreted as a new medical condition, and a second medication is prescribed to treat the side effect. Persons with Alzheimer's disease (AD) are at increased risk of prescribing cascades because they often have more medical conditions, more medications, and more complex care. The goal of this study was to evaluate mailed educational materials about prescribing cascades in persons with AD, and get input on their use in a future study. We interviewed 12 adults with AD, or prescribed a medication to treat AD, 14 caregivers of persons with AD, and 15 providers. We reviewed the interview transcripts to identify important findings about our educational materials. We edited the materials based on the interviews, and sent participating caregivers and providers a questionnaire to get their reactions to the new materials. Important findings from the interviews suggest: (a) Providers had conflicting views about the recommendations given; (b) Caregivers were likely to read letters addressed to patients; (c) Providers were likely to ignore letters, but were receptive to patients/caregivers introducing the topic; (d) Patients and caregivers had difficulty understanding prescribing cascades; (e) Providers worried mailed materials would undermine trust; (f) Participants had mixed views on how materials might affect a doctor's appointment; (g) Participants felt strongly that materials would improve patient/caregiver engagement. When surveyed, almost all providers found the revised materials informative and actionable; and most caregivers found them understandable and useful. These findings provide strong support for engaging caregivers to communicate with providers about prescribing cascades. The educational materials may help patients and caregivers prepare for a conversation with the provider, who can then tailor the discussion of the possible cascade to the specific needs of the individual patient and caregiver. However, evidence on whether materials can stimulate such conversations awaits testing in a future study.
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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 | 0.046 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".