Accurate, timely and reliable data are key to improving population health, and the data landscape in Austin is complex and continually evolving. The Division of Health Information and Data Analytic Science in the Department of Population Health provides a shared, central resource for accessing, curating and managing clinical and non-clinical health-related data for Dell Medical School, The University of Texas at Austin and the community.
Areas of Focus
The division supports the mission of Dell Med by accelerating innovation and research to improve health by:
- Developing people, processes and technologies to achieve efficiency and expertise in accessing, managing and curating data
- Integrating clinical and non-clinical data across the health spectrum and democratizing data for better decision-making
- Collaborating with researchers and community stakeholders to analyze, visualize and interpret data
The Data Integration team understands variations in data environments and implements creative solutions to achieve interoperability. It also facilitates access to data for clinicians, researchers and staff, which promotes patient care, encourages innovation and discovery and improves population health.
A critical function of this team is the Data Core, which serves as a shared resource and neutral data broker for accessing and managing data for Dell Med that:
- Continuously learns and understands internal and external data environments
- Possesses advanced skills to query, extract and manage datasets to make them readily usable for analysis
- Develops relationships and data use agreements with our partners to implement policies around data sharing, data storage and data reporting
- Establishes an efficient, transparent and user-friendly process to access data
- Strictly complies with all university, federal and state rules and regulations regarding the handling, storage and use of clinical and other data
Biomedical Data Science Hub
The Biomedical Data Science Hub collaborates with researchers, community stakeholders and the data integration team to use data more effectively and efficiently to improve health outcomes. These data scientists work closely with researchers to conceptualize and design studies and methods, then analyze and interpret large datasets to find answers to important, timely local questions that inform clinical and public health practice.
To that end, this team of computer, information and statistical scientists collaborates with researchers in four key areas:
- Clinical and population health biostatistics, including clinical trials
- Clinical research informatics
- Statistical genetics and genomics