The selection of data sources being made available as MedBus services has been driven by ongoing efforts to increase the capabilities of self-serve data access tools for UMHS clinical and translational research. These self-serve tools allow researchers to quickly identify potential cohorts of patients that could be enrolled in research studies, and to identify the available data and biosample resources for translational research. This work is being conducted in partnership with the Data Office for Clinical and Translational Research.
MedBus services such as the biospecimen service and waveform service allow for researchers to identify resources that may already be available for potential study participants. The development of these data interfaces as web services allow for federated data access to these resources regardless of the underlying location of these data. The development of an attestation service and training service provide the data to ensure that individuals accessing these data are doing so in a manner that is compliant with research projects that have been approved by the Institutional Review Board, and that they have completed the mandatory training required for access to ePHI data.
Additional information on how to access to these self-serve data tools are available through the UMHS Honest Broker Office.
MedBus services are aligned to NIH FAIR principles of developing a data commons infrastructure in which research data are Findable, Accessible, Interoperable and Reusable. The goal of this data commons is to build a digital ecosystem for biomedicine in which interoperapble services will accelerate discovery at the National level. The MedBus infrastructure for UMHS research data services will increase the efficiency and effectiveness of research within UMHS, and will further enable researchers to meet the data sharing requirements funding agencies.
MedBus projects are aligned to UM and UMHS initiatives around collaborative IT services including the comprehensive analytics services and support initiative. For example, we are working to establish definitions for common data elements used by MedBus in the UMHS Information Management Glossary, and we will be leveraging a central API manager as part of a university wide effort to centralize discovery of API services. We look forward to interacting with newly launched campus-wide efforts such as the Michigan Institute for Data Science and are eager to learn more about how we can integrate with efforts to increase interoperability of IT services across campus.