Medication reconciliation by pharmacist: database‐assisted MR vs unassisted MR: Discrepancy resolution (
Medication reconciliation by pharmacist: database‐assisted MR showed no clear difference in discrepancy resolution ( compared with unassisted MR (low certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Medication reconciliation by pharmacist: database‐assisted MR vs unassisted MR Discrepancy resolution ( · adults Medication reconciliation by pharmacist: database‐assisted MR showed no clear difference in discrepancy resolution ( compared with unassisted MR (low certainty). Reducing medication errors for adults in hospital settings (2021) · Cochrane Headline outcomes only | OR 1.37 [0.97, 1.93] | 2 studies · 791 participants | Low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Reducing medication errors for adults in hospital settings 2021 · Cochrane Headline outcomes only | Not reported | list not extracted yet | Not assessed |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
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.