ArticleCritical care nurse2018
Evaluation of User-Interface Alert Displays for Clinical Decision Support Systems for Sepsis.
Article in Critical care nurse, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Pooled it
- Implementation of Passive Deterioration Index Alerts in an Intermediate Care Unit: A Failed Early Warning System Strategy.Applied clinical informatics · 2025Article
- Barriers and facilitators to optimal sepsis care - a systematized review of healthcare professionals' perspectives.BMC health services research · 2025Review
- Human Factors Integration in Robotic Surgery.Human factors · 2024Review
- Information displays for automated surveillance algorithms of in-hospital patient deterioration: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Desired Characteristics of a Clinical Decision Support System for Early Sepsis Recognition: Interview Study Among Hospital-Based Clinicians.JMIR human factors · 2022Article
- Impact of an electronic alert system for pediatric sepsis screening a tertiary hospital experience.Scientific reports · 2022Article
- Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence-Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation.JMIR formative research · 2022Article
- Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System-Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses.JMIR human factors · 2022Article
- The Surviving Sepsis Campaign: research priorities for the administration, epidemiology, scoring and identification of sepsis.Intensive care medicine experimental · 2021Review
- Frontiers in human factors: embedding specialists in multi-disciplinary efforts to improve healthcare.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2021Article
- Clinical Decision Support and Implications for the Clinician Burnout Crisis.Yearbook of medical informatics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundHospitals are increasingly turning to clinical decision support systems for sepsis, a life-threatening illness, to provide patient-specific assessments and recommendations to aid in evidence-based clinical decision-making. Lack of guidelines on how to present alerts has impeded optimization of alerts, specifically, effective ways to differentiate alerts while highlighting important pieces of information to create a universal standard for health care providers.
objectiveTo gain insight into clinical decision support systems-based alerts, specifically targeting nursing interventions for sepsis, with a focus on behaviors associated with and perceptions of alerts, as well as visual preferences.
methodsAn interactive survey to display a novel user interface for clinical decision support systems for sepsis was developed and then administered to members of the nursing staff.
resultsA total of 43 nurses participated in 2 interactive survey sessions. Participants preferred alerts that were based on an established treatment protocol, were presented in a pop-up format, and addressed the patient's clinical condition rather than regulatory guidelines.
conclusionsThe results can be used in future research to optimize electronic medical record alerting and clinical practice workflow to support the efficient, effective, and timely delivery of high-quality care to patients with sepsis. The research also may advance the knowledge base of what information health care providers want and need to improve the health and safety of their patients.
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.