Literature DB >> 27480749

A methodology based on openEHR archetypes and software agents for developing e-health applications reusing legacy systems.

João Luís Cardoso de Moraes1, Wanderley Lopes de Souza2, Luís Ferreira Pires3, Antonio Francisco do Prado2.   

Abstract

BACKGROUND AND
OBJECTIVE: In Pervasive Healthcare, novel information and communication technologies are applied to support the provision of health services anywhere, at anytime and to anyone. Since health systems may offer their health records in different electronic formats, the openEHR Foundation prescribes the use of archetypes for describing clinical knowledge in order to achieve semantic interoperability between these systems. Software agents have been applied to simulate human skills in some healthcare procedures. This paper presents a methodology, based on the use of openEHR archetypes and agent technology, which aims to overcome the weaknesses typically found in legacy healthcare systems, thereby adding value to the systems.
METHODS: This methodology was applied in the design of an agent-based system, which was used in a realistic healthcare scenario in which a medical staff meeting to prepare a cardiac surgery has been supported. We conducted experiments with this system in a distributed environment composed by three cardiology clinics and a center of cardiac surgery, all located in the city of Marília (São Paulo, Brazil). We evaluated this system according to the Technology Acceptance Model.
RESULTS: The case study confirmed the acceptance of our agent-based system by healthcare professionals and patients, who reacted positively with respect to the usefulness of this system in particular, and with respect to task delegation to software agents in general. The case study also showed that a software agent-based interface and a tools-based alternative must be provided to the end users, which should allow them to perform the tasks themselves or to delegate these tasks to other people.
CONCLUSIONS: A Pervasive Healthcare model requires efficient and secure information exchange between healthcare providers. The proposed methodology allows designers to build communication systems for the message exchange among heterogeneous healthcare systems, and to shift from systems that rely on informal communication of actors to a more automated and less error-prone agent-based system. Our methodology preserves significant investment of many years in the legacy systems and allows developers to extend them adding new features to these systems, by providing proactive assistance to the end-users and increasing the user mobility with an appropriate support.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Archetypes; Pervasive healthcare; Semantic interoperability; Software agents; openEHR

Mesh:

Year:  2016        PMID: 27480749     DOI: 10.1016/j.cmpb.2016.07.013

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  4 in total

1.  Representation of Diagnosis and Nursing Interventions in OpenEHR Archetypes.

Authors:  Denilsen Carvalho Gomes; Nuno Abreu; Paulino Sousa; Claudia Moro; Deborah Ribeiro Carvalho; Marcia Regina Cubas
Journal:  Appl Clin Inform       Date:  2021-04-14       Impact factor: 2.342

2.  Discovering Clinical Information Models Online to Promote Interoperability of Electronic Health Records: A Feasibility Study of OpenEHR.

Authors:  Lin Yang; Xiaoshuo Huang; Jiao Li
Journal:  J Med Internet Res       Date:  2019-05-28       Impact factor: 5.428

3.  Prediction of COVID-19 diagnosis based on openEHR artefacts.

Authors:  Daniela Oliveira; Diana Ferreira; Nuno Abreu; Pedro Leuschner; António Abelha; José Machado
Journal:  Sci Rep       Date:  2022-07-22       Impact factor: 4.996

4.  Nutrition Information in Oncology - Extending the Electronic Patient-Record Data Set.

Authors:  Priscila A Maranhão; Ana Margarida Pereira; Conceição Calhau; Paula Ravasco; Federico Bozzetti; Alessandro Laviano; Liz Isenring; Elisa V Bandera; Maureen B Huhmann; Pedro Vieira-Marques; Ricardo J Cruz-Correia
Journal:  J Med Syst       Date:  2020-09-28       Impact factor: 4.460

  4 in total

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