Literature DB >> 29295283

Development of a Service-Oriented Sharable Clinical Decision Support System Based on Ontology for Chronic Disease.

Yong Shang1, Yu Wang1, Ling Gou1, Chengkai Wu1, Tianshu Zhou1, Jing-Song Li1.   

Abstract

Clinical decision support systems (CDSSs) have been proved as an efficient way to improve health care quality. However, the inflexibility in integrating multiple clinical practice guidelines (multi-CPGs), the mass input workload of patient data, and the difficulty in system sharing become barriers of CDSSs implementation. In this paper, we proposed a framework of CDSS for chronic disease based on ontology and service-oriented architecture (SOA) to improve these defects. We used ontology for knowledge base construction on multi-CPGs integration to overcome their differences as well as reduce the input procedure of patient data by ontology reasoning. Furthermore, we built the CDSS on an SOA structure to provide flexibility in system and data sharing, such that patients could get suggestions from the same system for self-management of chronic disease. A typical case was used to validate the CDSS functions and accuracy. Two clients were developed to illustrate the SOA superiority.

Entities:  

Keywords:  Biological Ontologies; Clinical Decision Support Systems

Mesh:

Year:  2017        PMID: 29295283

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  3 in total

1.  Importance of clinical decision support system response time monitoring: a case report.

Authors:  David Rubins; Adam Wright; Tarik Alkasab; M Stephen Ledbetter; Amy Miller; Rajesh Patel; Nancy Wei; Gianna Zuccotti; Adam Landman
Journal:  J Am Med Inform Assoc       Date:  2019-11-01       Impact factor: 4.497

Review 2.  Artificial Intelligence in Clinical Decision Support: a Focused Literature Survey.

Authors:  Stefania Montani; Manuel Striani
Journal:  Yearb Med Inform       Date:  2019-08-16

3.  Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis.

Authors:  Pavithra I Dissanayake; Tiago K Colicchio; James J Cimino
Journal:  J Am Med Inform Assoc       Date:  2020-01-01       Impact factor: 4.497

  3 in total

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