Your browser doesn't support javascript.
loading
Decentralized EHRs in the Semantic Web for Better Health Data Management.
Celuchova Bosanska, Dagmar; Huptych, Michal; Lhotská, Lenka.
Afiliação
  • Celuchova Bosanska D; Faculty of Biomedical Engineering, Czech Technical University in Prague, Czech Republic.
  • Huptych M; Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Czech Republic.
  • Lhotská L; Faculty of Biomedical Engineering, Czech Technical University in Prague, Czech Republic.
Stud Health Technol Inform ; 299: 157-162, 2022 Nov 03.
Article em En | MEDLINE | ID: mdl-36325857
ABSTRACT
Electronic Health Record (EHR) systems currently in use are not designed for widely interoperable longitudinal health data. Therefore, EHR data cannot be properly shared, managed and analyzed. In this article, we propose two approaches to making EHR data more comprehensive and FAIR (Findable, Accessible, Interoperable, and Reusable) and thus more useful for diagnosis and clinical research. Firstly, the data modeling based on the LinkML framework makes the data interoperability more realistic in diverse environments with various experts involved. We show the first results of how diverse health data can be integrated based on an easy-to-understand data model and without loss of available clinical knowledge. Secondly, decentralizing EHRs contributes to the higher availability of comprehensive and consistent EHR data. We propose a technology stack for decentralized EHRs and the reasons behind this proposal. Moreover, the two proposed approaches empower patients because their EHR data can become more available, understandable, and usable for them, and they can share their data according to their needs and preferences. Finally, we explore how the users of the proposed solution could be involved in the process of its validation and adoption.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Registros Eletrônicos de Saúde / Web Semântica Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Registros Eletrônicos de Saúde / Web Semântica Idioma: En Ano de publicação: 2022 Tipo de documento: Article