Comprehensive Summary
This study conducted by Manns et al. focused on evaluating the impact of pediatric clinical decision support systems, or CDSSs, in the emergency department with a specific interest in decision making accuracy, confidence, and response time. This study used the CDSS, "PED-IA", an ontology based system that utilizes a rule-driven inference engine which allows the system to logically produce a diagnosis on a given case. In addition, 51 practitioners assessed the same clinical cases both with and without the CDSS to determine PED-IA effectiveness. PED-IA was found to improve decision accuracy in practitioners by a total of 23.1%, and improve confidence levels by 0.65 points out of a 10 point scale. Response times increased as well on an average of 261.8 seconds per case. This CDSS left practitioners feeling satisfied with 88.2% reporting finding the system useful and 84.3% reporting they think it could reduce stress in clinical settings. Overall, after working with PED-IA, most clinicians see the positive effects and outcomes of utilizing this in practice; however, there is still a concern of the apparatus facing case fatigue or variability in case difficulty that needs to be further evaluated.
Outcomes and Implications
The study conducted by Manns et al. is important as overcrowding of pediatric emergency departments is a common occurrence. CDSS based responses can help enhance the accuracy, confidence, and response time when creating diagnoses, which can help practitioners find the most urgent cases in the emergency department while allowing for non-urgent cases to move through necessary steps in order to be treated. PED-IA has shown to improve triage accuracy which provides better care for patients, and can be used as a learning resource by leading practitioners through clinical reasoning. Currently, this system is still being evaluated on case difficulty and rate of fatigue.