UMB ICTR

The ICTR has partnered with informatics experts across campus to form the ICTR Informatics Core to offer all UMB campus faculty access up to 25 hours of free services to assist the research team in developing REDCap and Qualtrics data capture tools/database and data management, consultation on use of eHealth/mHealth/patient portal interventions, web-based research and usability testing, consultation to determine "best fit" of data projects and, more recently, cybersecurity and artificial Intelligence/machine learning consultation.

ACCESS TO CLINICAL DATA

• The Research HARBOR Data Warehouse consists of clinical and investigational data collected from a variety of data sources from UMMS, Translational Genomics Lab (TGL), iPatient, and other schools/entities across campus. Currently, the main data source is the Clinical Data Repository (CDR), which contains data from UMMC and other UMMS clinical sites. These data have been collated and are maintained as a library to allow researchers to request a broad scope of clinical, scientific, utilization, financial, and resource availability information. Additional data sources will become available within the Research HARBOR over time.  IRB approval/determination letter must be provided prior to initiating scope of work.

ACCESS TO NON-EHR DATA

• IQVIA Claims data
• Chronic Conditions Warehouser (CCW) data
• Medicare Current Beneficiary Survey (MCBS) data

CONSULTATION SERVICES ON

• Determining "best fit" of the proposed project and available databases
• Use of digital technology in support of health, such as mobile apps
• Use of eHealth/mHealth/patient portal interventions to promote and manage the health of adults age 50 and older
• Patient-centered PHR/patient portal implementation
• Web-based research and usability testing
• Hospital information systems evaluation and implementation

RESEARCH DATA CAPTURE TOOLS

• The REDCap team can help build a database for your project in REDCap.  Please be prepared to provide your current, IRB-approved research surveys, data entry /case report forms, and your project's data collection schedule.   Sample data collection forms. Data collected are stored and maintained locally on campus in a firewalled server managed by the UMB Clinical and Translational Research Informatics Center (CTRIC). REDCap provides automated export procedures for seamless data downloads to Excel, PDF, and common statistical packages (SPSS, SAS, Stata, R) as well as a built-in project calendar, a scheduling module, ad hoc reporting tools, and advanced features, such as auto-validation, branching logic, file uploading, calculated fields, and survey stop actions.  REDCap can be set up for multi-center studies as well.  
• Qualtrics - If you need a simple Q&A survey, consider Qualtrics
• Electronic data capture forms, consider OpenText TeleForm

UMBC will provide a new Cybersecurity and Artificial Intelligence (AI) Core to the UMB ICTR Informatics Core. In turn, UMBC faculty will become eligible for many of the existing resources offered by the ICTR to UMB researchers who are currently preparing or executing clinical translational research.  The new UMBC services will be an exciting addition for those researchers exploring the use of machine learning (ML) and AI to identify patterns in data and make decisions with minimal human intervention.   For researchers interested in developing apps and devices that may improve delivery and exchange of health information, UMBC's Cybersecurity expertise will help the researcher protect those devices, systems, and data from attack.  See below for a list of UMBC Core services available to UMB researchers.

UMBC - ICTR Core Capabilities

• Securing medical devices
• Securing smart systems, e.g., smart surgery rooms
• Protecting learned/predictive models from attacks
• Deep learning and artificial neural networks
• Natural language processing
• Graph analytics
• Time series analytics
• Data visualization augmented reality and virtual reality

UMBC - ICTR Core Example of Services:

• Consult to uncover possible cybersecurity risks associated with devices and/or systems.
• Consult on ways to protect devices and/or systems from attackers, either at design time or after deployment.
• Consult on ways to apply artificial intelligence and machine learning to solve specific problems given existing data, including processing pipelines, specific algorithms, and evaluation methodology
• Advise on what additional data could be collected or obtained to potentially improve the utility of AI/ML for specific use cases.
• Construct simple proof-of-concept AI/ML systems to understand what level of performance might be achieved with more time, data, or resources
• Advise on the best visual representations to explore complex datasets and to communicate results to others.