ArticleNPJ digital medicine2025
An openEHR based infection control system to support monitoring of nosocomial bacterial clusters and contacts.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- A Data-Centric Approach for Health Care and Research in a Health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study.JMIR medical informatics · 2026Article
- Toward a human-centered digital ecosystem: bridging the "AI Chasm" in intelligent nosocomial infection monitoring.Frontiers in public health · 2026Article
- Human-centered digital ecosystem: safeguarding healthcare workers' sleep, ergonomics, and occupational health.Frontiers in public health · 2026Article
- Association between infection prevention and control safety culture and healthcare workers' compliance with infection control measures: a cross-sectional study.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Early outbreak detection, allowing rapid intervention, is essential to reduce the burden of healthcare-associated pathogen transmission, including multidrug-resistant bacteria. Digital, routine data-driven solutions are promising, but often proprietary, non-interoperable, or limited in functional scope. The open-source Smart Infection Control System (SmICS) offers automatic calculations and interactive views on patients' movement and lab data, epidemic curves, contact networks, complemented by temporal-spatial visualizations. It is an open-source software based on openEHR as an interoperability standard and was evaluated by assessing time efficiencies in performing basic infection control tasks (e.g., contact networks) and usability with the System Usability Scale (SUS). Evaluated at three sites, SmICS reduced the time needed for performing routine infection control tasks by up to 81.47% (68.5 min (95%CI [30.5-106.5])) reaching a SUS of 51.6 points. The study reveals time savings through the use of SmICS in daily tasks, but also identified usability issues and a need for minimizing query waiting times.
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.