Articlenpj antimicrobials and resistance2025
A mixed methods evaluation of an antimicrobial prescribing clinical decision support system app.
Article in npj antimicrobials and resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Antibiotic Escalation Following Rapid Multiplex PCR Pneumonia Panel Testing in Intensive Care Patients with Severe Pneumonia: A Retrospective Cohort Study.Antibiotics (Basel, Switzerland) · 2026Article
- Editorial: Machine learning and AI-driven insights into microbial pathogenesis and drug resistance.Frontiers in cellular and infection microbiology · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study evaluated how the usability and accessibility of a digital antimicrobial prescribing app influences clinical decision-making. Using a convergent parallel mixed methods design, the study assessed app usage patterns with surveys and interviews to identify common barriers. Among 700 users at a tertiary hospital, 61 completed the survey (7.3% response rate), including 52 prescribers. Additionally, 20 prescribers participated in interviews. While 87% found the guidelines relevant, only 52% rated navigation as easy, and 34% reported slower decision-making compared to other clinical decision support systems (CDSS). App use peaked during morning rounds (8-11 AM). Key challenges included navigation inefficiencies (59%), technical barriers, limited onboarding, and concerns around clinical AI transparency. Interviews highlighted frustration with excessive steps and a desire for simpler guideline access. Findings highlight the need for user-friendly CDSS tools integrated into clinical workflows, and stress the importance of stakeholder co-design to improve medication safety.
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.