Data Use Agreement & Compliance Specialist

The Institute for Healthcare Policy and Innovation (IHPI) supports health services research across the University of Michigan campus. IHPI’s Data & Methods Hub (DMH) was created to provide a number of unique support services, including access to high-value datasets, methodological support, and assistance with data use agreements, to help build a vigorous and supportive research community. The DMH currently supports approximately 400 faculty and research staff across all UM departments, all of whom depend on continuous, compliant access to restricted data resources.

To support these services, DMH is seeking a full‑time Data Use Agreement & Compliance Specialist to carry out the administrative activities related to data use agreement (DUA) requests, maintenance, data resource onboarding, and permissions management. This position plays a critical role in ensuring IHPI researchers have timely, compliant access to restricted datasets. DMH maintains a repository of data, including but not limited to: CMS Research Identifiable Files (RIF), CMS Limited Datasets (LDS), Merative Market Scan, AHRQ HCUP State and Nationwide Databases, Truveta EHR data.

This position focuses mainly on the use of CMS data resources but may assist with requests across the data portfolio.

Individuals in this role will work alongside supportive DMH colleagues who can help answer questions, brainstorm ideas for process improvement, and provide professional development opportunities. We are a flexible, trust‑driven team! This is an excellent opportunity for someone who desires a career in health services research administration and data governance.

This position is located at the North Campus Research Complex; however, applicants will have the option of a hybrid or remote work schedule.

This role includes, but is not limited to, the following activities.

• Manage restricted data reuse across multiple active DUAs, including assessing encryption schema compatibility, coordinating cohort selection to align with permitted uses, and cross‑referencing prior application materials to support efficient, compliant reuse of CMS RIF and other federal data holdings.
• Demonstrated expertise managing Data Use Agreements (DUAs) across the request lifecycle, including independently preparing, reviewing, and submitting applications, amendments, and renewals in compliance with the requirements of data providers (CMS, MDHHS, AHRQ, etc).
• Knowledge of CMS data assets and their utility including:
  Medicare fee‑for‑service, Medicare Advantage, Medicaid TAF, linked‑survey data, and their application in health services research, with the ability to advise researchers on appropriate use, analytic strengths and limitations, and data selection across project types.
• Comprehensive understanding of CMS data privacy, security, and disclosure requirements, including HIPAA compliance, CMS cell suppression and data release guidelines, and the application of these standards across a portfolio of active agreements and research environments.
• Serve as the primary point of coordination across multiple stakeholders, including PIs, project staff, UM Office of Research and Sponsored Projects (ORSP), IT, and data vendors, managing documentation workflows and communication across involved parties.

• Organize process flows, user manuals, and data dictionaries. Maintain reference materials to support researcher requests and use of IHPI‑managed data resources.
• Update documentation to reflect changes in data asset availability, variable definitions, access requirements, and DUA terms.
• Ensure support materials are accurate, accessible, and sufficient to enable researchers to independently navigate data access and use requirements.

• Coordinate receipt, transformation, and storage of incoming datasets, ensuring data are processed and stored in accordance with data security requirements.
• Work with IT staff to maintain the DMH central data repository, manage storage, and identify opportunities to archive resources.
• Create and manage permission groups across multiple compute…