Question · asked by 1 review
Educational policy: mailed educational materials on prescribing for physicians and HMO members vs no educational intervention: Costs
- Population
- prescribers or patients that are subjected to regulatory and educational interventions in prescribing due to government, non‐government or third party payer policies
- Intervention
- Educational policy: mailed educational materials on prescribing for physicians and HMO members
- Comparison
- no educational intervention
- Outcome
- Costs
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Educational policy: mailed educational materials on prescribing for physicians and HMO members vs no educational intervention Costs · prescribers or patients that are subjected to regulatory and educational interventions in prescribing due to… Pharmaceutical policies: effects of educational or regulatory policies targeting prescribers (2019) · Cochrane Headline outcomes only | no estimate extracted | 1 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Pharmaceutical policies: effects of educational or regulatory policies targeting prescribers 2019 · Cochrane Headline outcomes only | Not reported | Not extracted | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Educational policy: mailed educational materials on prescribing for physicians and HMO members vs mailed educational materials on prescribing · prescribers or patients that are subjected to educational or regulatory interventions in… · 1 review
- Educational policy: mailed educational materials on prescribing for physicians and HMO members vs an intervention to regulate drug reimbursement · prescribers or patients that are subjected to educational or regulatory interventions in… · 1 review
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.