Publication: A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study.
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Identifiers
Date
2022-08-02
Authors
Roman-Villaran, Esther
Alvarez-Romero, Celia
Martinez-Garcia, Alicia
Escobar-Rodriguez, German Antonio
Garcia-Lozano, Maria Jose
Baron-Franco, Bosco
Moreno-Gaviño, Lourdes
Moreno-Conde, Jesus
Rivas-Gonzalez, Jose Antonio
Parra-Calderon, Carlos Luis
Advisors
Journal Title
Journal ISSN
Volume Title
Publisher
JMIR Publications, Inc.
Abstract
Due to an increase in life expectancy, the prevalence of chronic diseases is also on the rise. Clinical practice guidelines (CPGs) provide recommendations for suitable interventions regarding different chronic diseases, but a deficiency in the implementation of these CPGs has been identified. The PITeS-TiiSS (Telemedicine and eHealth Innovation Platform: Information Communications Technology for Research and Information Challenges in Health Services) tool, a personalized ontology-based clinical decision support system (CDSS), aims to reduce variability, prevent errors, and consider interactions between different CPG recommendations, among other benefits. The aim of this study is to design, develop, and validate an ontology-based CDSS that provides personalized recommendations related to drug prescription. The target population is older adult patients with chronic diseases and polypharmacy, and the goal is to reduce complications related to these types of conditions while offering integrated care. A study scenario about atrial fibrillation and treatment with anticoagulants was selected to validate the tool. After this, a series of knowledge sources were identified, including CPGs, PROFUND index, LESS/CHRON criteria, and STOPP/START criteria, to extract the information. Modeling was carried out using an ontology, and mapping was done with Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) and Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT; International Health Terminology Standards Development Organisation). Once the CDSS was developed, validation was carried out by using a retrospective case study. This project was funded in January 2015 and approved by the Virgen del Rocio University Hospital ethics committee on November 24, 2015. Two different tasks were carried out to test the functioning of the tool. First, retrospective data from a real patient who met the inclusion criteria were used. Second, the analysis of an adoption model was performed through the study of the requirements and characteristics that a CDSS must meet in order to be well accepted and used by health professionals. The results are favorable and allow the proposed research to continue to the next phase. An ontology-based CDSS was successfully designed, developed, and validated. However, in future work, validation in a real environment should be performed to ensure the tool is usable and reliable.
Description
MeSH Terms
Atrial Fibrillation
Systematized Nomenclature of Medicine
Decision Support Systems, Clinical
Anticoagulants
Global Health
Health Level Seven
Polypharmacy
Prevalence
Drug Prescriptions
Chronic Disease
Systematized Nomenclature of Medicine
Decision Support Systems, Clinical
Anticoagulants
Global Health
Health Level Seven
Polypharmacy
Prevalence
Drug Prescriptions
Chronic Disease
DeCS Terms
Enfermedad crónica
Pacientes
Investigación
Polifarmacia
Informes de casos
Prescripciones de medicamentos
Creatividad
Lista de medicamentos potencialmente inapropiados
Esperanza de vida
Fibrilación Atrial
Pacientes
Investigación
Polifarmacia
Informes de casos
Prescripciones de medicamentos
Creatividad
Lista de medicamentos potencialmente inapropiados
Esperanza de vida
Fibrilación Atrial
CIE Terms
Keywords
CDSS, adherence, anticoagulants, atrial fibrillation, clinical decision support system, complex chronic patients, functional validation, multimorbidity, ontology, polypharmacy
Citation
Román-Villarán E, Alvarez-Romero C, Martínez-García A, Escobar-Rodríguez GA, García-Lozano MJ, Barón-Franco B, et al. A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study. JMIR Form Res. 2022 Aug 2;6(8):e27990