Literature DB >> 25532198

Exploiting Semantic Web Technologies to Develop OWL-Based Clinical Practice Guideline Execution Engines.

Borna Jafarpour, Samina Raza Abidi, Syed Sibte Raza Abidi.   

Abstract

Computerizing paper-based CPG and then executing them can provide evidence-informed decision support to physicians at the point of care. Semantic web technologies especially web ontology language (OWL) ontologies have been profusely used to represent computerized CPG. Using semantic web reasoning capabilities to execute OWL-based computerized CPG unties them from a specific custom-built CPG execution engine and increases their shareability as any OWL reasoner and triple store can be utilized for CPG execution. However, existing semantic web reasoning-based CPG execution engines suffer from lack of ability to execute CPG with high levels of expressivity, high cognitive load of computerization of paper-based CPG and updating their computerized versions. In order to address these limitations, we have developed three CPG execution engines based on OWL 1 DL, OWL 2 DL and OWL 2 DL + semantic web rule language (SWRL). OWL 1 DL serves as the base execution engine capable of executing a wide range of CPG constructs, however for executing highly complex CPG the OWL 2 DL and OWL 2 DL + SWRL offer additional executional capabilities. We evaluated the technical performance and medical correctness of our execution engines using a range of CPG. Technical evaluations show the efficiency of our CPG execution engines in terms of CPU time and validity of the generated recommendation in comparison to existing CPG execution engines. Medical evaluations by domain experts show the validity of the CPG-mediated therapy plans in terms of relevance, safety, and ordering for a wide range of patient scenarios.

Entities:  

Mesh:

Year:  2014        PMID: 25532198     DOI: 10.1109/JBHI.2014.2383840

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  6 in total

1.  A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

Authors:  Samina Abidi
Journal:  J Med Syst       Date:  2017-10-26       Impact factor: 4.460

2.  Protocol-Driven Decision Support within e-Referral Systems to Streamline Patient Consultation, Triaging and Referrals from Primary Care to Specialist Clinics.

Authors:  Ehsan Maghsoud-Lou; Sean Christie; Samina Raza Abidi; Syed Sibte Raza Abidi
Journal:  J Med Syst       Date:  2017-08-01       Impact factor: 4.460

3.  When there is Confusion and Conflicts - Ask Delphi!

Authors:  Venkatachalam Raveenthiran; Yogesh Kumar Sarin
Journal:  J Neonatal Surg       Date:  2015-07-01

4.  Building an Ontology for Identity Resolution in Healthcare and Public Health.

Authors:  Jeffrey Duncan; Karen Eilbeck; Scott P Narus; Stephen Clyde; Sidney Thornton; Catherine Staes
Journal:  Online J Public Health Inform       Date:  2015-07-01

5.  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

Review 6.  The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review.

Authors:  Eda Bilici; George Despotou; Theodoros N Arvanitis
Journal:  Digit Health       Date:  2018-10-03
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.