ReviewWorld journal of critical care medicine2016
Clinical decision support for drug related events: Moving towards better prevention.
Review in World journal of critical care medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Characterization of children's prospective prescription review and exploration of factors influencing the success of interventions.Therapeutic advances in drug safety · 2025Article
- Detection of Drug-Related Problems through a Clinical Decision Support System Used by a Clinical Pharmacy Team.Healthcare (Basel, Switzerland) · 2023Article
- Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects.Medical journal of the Islamic Republic of Iran · 2021Review
- "They Don't Trust Us": The Influence of Perceptions of Inadequate Nursing Home Care on Emergency Department Transfers and the Potential Role for Telehealth.Clinical nursing research · 2020Article
- Effect of Best Practice Advisories on Sedation Protocol Compliance and Drug-Related Hazardous Condition Mitigation Among Critical Care Patients.Critical care medicine · 2020Observational
- Local, Early, and Precise: Designing a Clinical Decision Support System for Child and Adolescent Mental Health Services.Frontiers in psychiatry · 2020Article
- Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study.BMC medical informatics and decision making · 2019Article
- Exploring the Impact of the Prescription Automatic Screening System in Health Care Services: Quasi-Experiment.JMIR medical informatics · 2019Article
- Trigger alerts associated with laboratory abnormalities on identifying potentially preventable adverse drug events in the intensive care unit and general ward.Therapeutic advances in drug safety · 2018Article
- Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016.Yearbook of medical informatics · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Clinical decision support (CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors (ME) and adverse drug events (ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.
Indexed as
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.