MSCA ELITE-S Fellow
Dublin City University
Subhashis Das is a postdoctoral researcher at Centre for e-Integrated Care (CeIC), Dublin city university since March 2020. He started as an ELITE-S Marie-Curie postdoctoral fellow at ADAPT Centre @DCU and Centre for e-Integrated Care (CeIC) from 1st July 2020. Dr. Das has been a member of the National Standards Authority of Ireland (NSAI)-Health Informatics Standards Consultative Committee (HISC) since March 2020. He is also a member of the European Committee for Standardization (CEN)/TC 251-Health informatics and International Organization for Standardization (ISO)/TC 215–Health informatics since June 2020. He has been an active participant in W3C Semantic Web Health Care and Life Sciences Community Group (HCLS CG) since October 2019.
Dr. Das was a data scientist in the KnowDive Group at the Department of Information Engineering and Computer Science (DISI), Università degli Studi di Trento, Italy working on the InteropEHRate, an EU-Horizon 2020 project. InteropEHRate project listed under European Commission Innovation Radar in 2020. He obtained his Ph.D. from the ICT-Doctoral School, University of Trento, Trento, Italy. His research interests focus on ontology, information science, and health informatics. He has working experience in the healthcare sector having worked at NHS-Scotland, School of Informatics, University of Edinburgh, UK. He was a teaching associate professional at the Department of Information Engineering and Computer Science (DISI), University of Trento, Trento, Italy. Teaching assistant and guiding project for the MSc course on Data and Knowledge Integration ( 2016-2019).
A Common Semantic Data Model (CSDM) for complex Healthcare Network
The amount of data collected in the electronic healthcare record (EHR) about an individual’s health state has grown exponentially over recent decades. Access to EHR information is no longer required solely in secondary care clinics and hospitals, but are also needed by the individual service user and their families, healthcare organizations and primary care teams to deliver self-management support in the home.
The relationships between the systems which provide access to data and the actors who access the data from the systems need to be carefully designed to understand the relational effect and impact between humans and non- humans’ agents such as IoT. In this diverse data enrich the healthcare network. Actor-Network Theory (ANT) helps us to distinguish how one-factor may influence others within a social process workflow.
Specifically, ANT can contribute to understanding how inanimate entities (IoT) can effect and impact on the social process of care and associated impact on behavioral change. But ANT can only provide one aspect of understanding this complex process in context. It does not provide a solution for the integration of multiple sources of data across a diverse range of resources which is considered the main challenge. Standard-based approaches try to solve the data heterogeneity problem by enforcing all stakeholders engaged in service delivery to use the same specifications and techniques.
Realistically, such an approach is proving challenging and complex. To achieve interoperability across one to many platforms by transforming all data into a single standard capturing all features, properties, and data fields in a single schema model is multifaceted and involves a number of stakeholders. In this proposal, a Common Semantic Data Model (CSDM) for complex Healthcare networks, we propose a hybrid approach to tackle the complexity based on two popular standards, FHIR and OMOP to accommodate the maximum amount of data fields in every aspect of healthcare experiment.