Leveraging telehealth in underserved populations for open data research
By Linda Larson-Prior, University of Arkansas for Medical Sciences
Theme: Open Data 2.0
Format: Lightning talk
Abstract
This Lightning talk will introduce an innovative method for remote collection of research data from rural and underserved populations who are under-represented in clinically-relevant research. Our study is focused on Parkinson’s disease (PD), a progressive neurodegenerative disorder with significant adverse effects on movement, general health and cognitive function. We are taking advantage of a strong telehealth presence and a program launched to provide telehealth services to PD patients for whom travel to the Movement Disorders Clinic at the University of Arkansas for Medical Sciences is a significant burden. Research data will be imported to the Arkansas Image Enterprise System (ARIES), a neuroinformatics research platform and repository hosting neuroimaging data integrated with diverse multi-modal non-image data relevant to neuroinformatics investigations. Data will include image-derived features, various motor assessments, cognitive assessments, mood and quality of life questionnaires along with de-identified clinical data from electronic health records. ARIES is an instantiation of the Platform for Imaging in Precision Medicine (PRISM) which containerizes and extends the technology underlying The Cancer Image Archive. ARIES uses Open Biomedical Ontologies to semantically integrate clinical and research non-image data, and image metadata, into a single knowledge graph. The result is a repository of semantically integrated data that is Findable, Accessible, Interoperable, and Reusable (FAIR). The ARIES platform provides an integrated collection of fully de-identified, well curated, multi-modal data that can be openly shared.
jsheunis
commented
4 years ago
Leveraging telehealth in underserved populations for open data research
By Linda Larson-Prior, University of Arkansas for Medical Sciences
Abstract
This Lightning talk will introduce an innovative method for remote collection of research data from rural and underserved populations who are under-represented in clinically-relevant research. Our study is focused on Parkinson’s disease (PD), a progressive neurodegenerative disorder with significant adverse effects on movement, general health and cognitive function. We are taking advantage of a strong telehealth presence and a program launched to provide telehealth services to PD patients for whom travel to the Movement Disorders Clinic at the University of Arkansas for Medical Sciences is a significant burden. Research data will be imported to the Arkansas Image Enterprise System (ARIES), a neuroinformatics research platform and repository hosting neuroimaging data integrated with diverse multi-modal non-image data relevant to neuroinformatics investigations. Data will include image-derived features, various motor assessments, cognitive assessments, mood and quality of life questionnaires along with de-identified clinical data from electronic health records. ARIES is an instantiation of the Platform for Imaging in Precision Medicine (PRISM) which containerizes and extends the technology underlying The Cancer Image Archive. ARIES uses Open Biomedical Ontologies to semantically integrate clinical and research non-image data, and image metadata, into a single knowledge graph. The result is a repository of semantically integrated data that is Findable, Accessible, Interoperable, and Reusable (FAIR). The ARIES platform provides an integrated collection of fully de-identified, well curated, multi-modal data that can be openly shared.
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