Rule Management in Clinical Decision Support Expert System for the Alzheimer Disease

2016 ◽  
pp. 465-477 ◽  
Author(s):  
Firas Zekri ◽  
Rafik Bouaziz
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Alzheimer Disease ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Rule Management

Bridging the gap between evidence and practice in asthma management by developing a mobile-based clinical decision support system for GINA asthma guideline

2020 ◽  
Author(s):  
Marsa Gholamzadeh ◽  
Hamidreza Abtahi ◽  
Shahideh Amini ◽  
Mehrnaz Asadi Gharabaghi
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Clinical Decision Making ◽  
Asthma Management ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Care Providers ◽  
Asthma Guideline

Abstract Background Physicians’ compliance with clinical practice guidelines (CPG) remains insufficient. Guideline-based clinical decision support systems (CDSSs) can be beneficial to address this challenge. The principal objective of this research is to translate the Global Initiative for Asthma guideline (GINA) into a mobile-based CDSS to improve its utilization as a clinical decision-making tool.Methods Designing and development of our expert system were conducted in an iterative and stepwise approach by the multidisciplinary expert team. Translating and extracting the embedded knowledge in GINA was done according to the Knowledge to Action framework. Next, extracted knowledge was converted to decision tree models to design the knowledge-base of the desired system. The accuracy and proficiency of the expert system were calculated based on the predefined scenarios. The expert system usability was evaluated by the think-aloud protocol and the GUIDES questionnaire.Results Based on the analysis of the GINA guideline, more than 220 rules and 336 knowledge statements were extracted. Our knowledge-based expert system was devised based on production rules. After modification with feedback from six experts, the system was developed in the Android platform. The overall accuracy and efficiency of our CDSS were 100% and 100%, respectively.Conclusion The ginasthma mobile-based CDSS was developed for android smartphones to improve the adherence of health care providers to GINA guideline with high accuracy and efficiency. Further investigation is needed to evaluate the efficacy of this app in real practice.

Clinical decision support

2013 ◽  
Vol 46 (2) ◽  
pp. 52
Author(s):  
CHRISTOPHER NOTTE ◽  
NEIL SKOLNIK
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision
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