Abstract
Healthcare data includes information about patients’ life style, medical history, claims data, metabolomics and genomics profiles. Adequate and analytic access to healthcare data has potential to revolutionize the field of medicine by detecting diseases at earlier stages and modelling complex biological interactions by integrating and analyzing knowledge in a holistic manner. To improve the quality and transition of healthcare at reduced cost, innovative platforms are necessary to analyze heterogeneous clinical data of huge volume, velocity, variety and veracity. Healthcare data analytic process implementation is not straightforward and to effectively implement it, various big data challenges have to be overcome, which requires significant efforts from the experts in various disciplines. In response to these challenges and promoting significant medical transformation in public health, we showcase a new HIPAA compliant and high performance computing based large scaled big data system: Management, Analysis and Visualization of Clinical Data (MAV-clic), developed at UConn Health. MAV-clic successfully implements healthcare data analytic process and major analytic functionalities dealing with healthcare data consisting of three different modules: Cohort building, Data analysis, and Customized Measurement analysis. MAV-clic contains medical history of over 800,000 patients, and information about over all providers, medications and diagnosis codes. To fulfill the growing interests in implementing the health information system, MAV-clic fulfills the requirements of data owners as well as data users in the healthcare system. To give better understanding of the MAV-clic, we highlight background, and discuss its system designs, methods, development details and analysis capabilities in this manuscript.