Abstract
BackgroundFrailty is a common clinical syndrome in ageing population that carries an increased risk for adverse health outcomes including falls, hospitalization, disability, and mortality. As these outcomes affect the health and social care planning, during the last years there is a tendency of investing in monitoring and preventing strategies. Although a number of electronic health record (EHR) systems have been developed, including personalized virtual patient models, there are limited ageing population oriented systems.MethodsWe exploit the openEHR framework for the representation of frailty in ageing population in order to attain semantic interoperability, and we present the methodology for adoption or development of archetypes. We also propose a framework for a one-to-one mapping between openEHR archetypes and a column-family NoSQL database (HBase) aiming at the integration of existing and newly developed archetypes into it.ResultsThe requirement analysis of our study resulted in the definition of 22 coherent and clinically meaningful parameters for the description of frailty in older adults. The implemented openEHR methodology led to the direct use of 22 archetypes, the modification and reuse of two archetypes, and the development of 28 new archetypes. Additionally, the mapping procedure led to two different HBase tables for the storage of the data.ConclusionsIn this work, an openEHR-based virtual patient model has been designed and integrated into an HBase storage system, exploiting the advantages of the underlying technologies. This framework can serve as a base for the development of a decision support system using the openEHR’s Guideline Definition Language in the future.
Highlights
Frailty is a common clinical syndrome in ageing population that carries an increased risk for adverse health outcomes including falls, hospitalization, disability, and mortality
By utilizing the openEHR modeling approach for FrailSafe, virtual modeling of older people can be performed using a stable reference model (RM) [22] as a general framework, and this direction can be advantageous from multiple points of view: 1. It enables the use of archetypes as domain information to achieve greater flexibility and stability, as they can efficiently be adopted in problems like frailty prediction, in which the domain concepts are vast in number, have complex relationships, and evolve continuously
The summary of archetypes from this work are shared in a public open source repository [52] and can be used by other researchers/clinicians/developers for the representation of clinical information that can be processed by their systems and this work enables semantic interoperability [53] for ageing-related systems that will be developed in the future
Summary
Frailty is a common clinical syndrome in ageing population that carries an increased risk for adverse health outcomes including falls, hospitalization, disability, and mortality. As these outcomes affect the health and social care planning, during the last years there is a tendency of investing in monitoring and preventing strategies. One of the key aspects in such systems is to store medical data efficiently in order to capture health status across time Towards this direction, a number of electronic health records (EHR), or electronic medical records (EMR), have been developed. The European Commission’s eHealth Action Plan 2012-2020 promotes semantic interoperability of EHR systems as a crucial challenge in eHealth solutions [12,13,14,15,16] in an effort to provide a roadmap to empower patients and healthcare workers
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