RESUMO
The wide gap between a care provider's conceptualization of electronic health record (EHR) and the structures for electronic health record (EHR) data storage and transmission, presents a multitude of obstacles for development of innovative Health IT applications. While developers model the EHR view of the clinicians at one end, they work with a different data view to construct health IT applications. Although there has been considerable progress to bridge this gap by evolution of developer friendly standards and tools for terminology mapping and data warehousing, there is a need for a simplified framework to facilitate development of interoperable applications. To this end, we propose a framework for creating a layer of semantic abstraction on the EHR and describe preliminary work on the implementation of this framework for management of hyperlipidemia and hypertension. Our goal is to facilitate the rapid development and portability of Health IT applications.
RESUMO
We live in the genomic era of medicine, where a patient's genomic/molecular data is becoming increasingly important for disease diagnosis, identification of targeted therapy, and risk assessment for adverse reactions. However, decoding the genomic test results and integrating it with clinical data for retrospective studies and cohort identification for prospective clinical trials is still a challenging task. In order to overcome these barriers, we developed an overarching enterprise informatics framework for translational research and personalized medicine called Synergistic Patient and Research Knowledge Systems (SPARKS) and a suite of tools called Oncology Data Retrieval Systems (OncDRS). OncDRS enables seamless data integration, secure and self-navigated query and extraction of clinical and genomic data from heterogeneous sources. Within a year of release, the system has facilitated more than 1500 research queries and has delivered data for more than 50 research studies.
