Articlenpj health systems2025
Analytical approaches for medication management for patient safety: a scoping review.
Article in npj health systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- AI-Based Automation for Medication Reconciliation: Scoping Review.Journal of medical Internet research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Safe medication management is a cornerstone of high-quality patient care, yet it remains one of the most complex and challenging components of healthcare delivery. This scoping review investigates analytical approaches for patient safety-focused medication management, with an emphasis on artificial intelligence and decision-theoretic methods. Guided by PRISMA-ScR, we searched PubMed, Web of Science, ACM, INFORMS, IEEE, and CINAHL for English-language studies published through December 2023. We identified 64 unique studies, over half of which were published since 2020, with 27% based in the United States. Across all studies, 49% addressed adverse drug event detection or prediction, 24% focused on medication error detection, and 13% examined medication reconciliation or review. The remainder explored related areas such as polypharmacy management, dosage adjustment, and medication recommendation. Although artificial intelligence methods were widely applied, only 7 studies used decision-theoretic frameworks, and just 5 combined both approaches. Overall, the literature reflects a predominant focus on single-drug event detection but limited research on managing incomplete or inaccurate medication lists across patient encounters. Future work should explore the combination of predictive, prescriptive, and generative analytics by integrating traditional machine learning, generative AI, and decision-theoretic methods to advance a more comprehensive safe medication management.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.