Trial reportInternational journal of medical informatics2014
Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency department: a randomized clinical trial.
Trial report in International journal of medical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 7 of them syntheses 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
25 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Pediatric Predictive Artificial Intelligence Implemented in Clinical Practice from 2010 to 2021: A Systematic Review.Applied clinical informatics · 2025Pooled it
- Applications of machine learning approaches for pediatric asthma exacerbation management: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- The role of information systems in emergency department decision-making-a literature review.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- eHealth Tools That Assess and Track Health and Well-being in Children and Young People: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Pooled it
- Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.Annals of emergency medicine · 2019Pooled it
- Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Improving patient outcomes through quality improvement and safety culture interventions in pediatric emergency care: a systematic review of best practices.International journal of emergency medicine · 2025Review
- Application of a user experience design approach for an EHR-based clinical decision support system.JAMIA open · 2024Article
- Implemented machine learning tools to inform decision-making for patient care in hospital settings: a scoping review.BMJ open · 2023Article
- Recent trends of healthcare information and communication technologies in pediatrics: a systematic review.Clinical and experimental pediatrics · 2022Article
- Implementation of a structured emergency nursing framework results in significant cost benefit.BMC health services research · 2021Article
- Article
- Impact of a care bundle for patients with blunt chest injury (ChIP): A multicentre controlled implementation evaluation.PloS one · 2021Observational
- Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.Methods of information in medicine · 2020Article
- Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review.JMIR medical informatics · 2020Review
- Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Patients Decision Aid System Based on FHIR Profiles.Journal of medical systems · 2018Article
- Identifying Asthma Exacerbation-Related Emergency Department Visit Using Electronic Medical Record and Claims Data.Applied clinical informatics · 2018Article
- Data Capture and Analysis of Signs and Symptoms in a Chemically Exposed Population.Journal of informatics nursing · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
objectiveThe use of evidence-based guidelines can improve the care for asthma patients. We implemented a computerized asthma management system in a pediatric emergency department (ED) to integrate national guidelines. Our objective was to determine whether patient eligibility identification by a probabilistic disease detection system (Bayesian network) combined with an asthma management system embedded in the workflow decreases time to disposition decision.
methodsWe performed a prospective, randomized controlled trial in an urban, tertiary care pediatric ED. All patients 2-18 years of age presenting to the ED between October 2010 and February 2011 were screened for inclusion by the disease detection system. Patients identified to have an asthma exacerbation were randomized to intervention or control. For intervention patients, asthma management was computer-driven and workflow-integrated including computer-based asthma scoring in triage, and time-driven display of asthma-related reminders for re-scoring on the electronic patient status board combined with guideline-compliant order sets. Control patients received standard asthma management. The primary outcome measure was the time from triage to disposition decision.
resultsThe Bayesian network identified 1339 patients with asthma exacerbations, of which 788 had an asthma diagnosis determined by an ED physician-established reference standard (positive predictive value 69.9%). The median time to disposition decision did not differ among the intervention (228 min; IQR=(141, 326)) and control group (223 min; IQR=(129, 316)); (p=0.362). The hospital admission rate was unchanged between intervention (25%) and control groups (26%); (p=0.867). ED length of stay did not differ among intervention (262 min; IQR=(165, 410)) and control group (247 min; IQR=(163, 379)); (p=0.818).
conclusionsThe control and intervention groups were similar in regards to time to disposition; the computerized management system did not add additional wait time. The time to disposition decision did not change; however the management system integrated several different information systems to support clinicians' communication.
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