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NORC at the University Chicago

Chris Cox

Pronouns: She/Her

Senior Fellow
Health Care Programs
Chris is focused on increasing data utility and access through data linkage and disclosure prevention technologies.

Chris is a senior fellow in the Health Care Programs department at NORC at the University of Chicago. After a 35 year federal career focused on increasing data utility and access to drive health system transformation and improve health outcomes, Chris joined NORC, bringing her broad expertise and knowledge of data analysis and integration across federal and state health data systems.

During her tenure in the federal sector, Chris served as the Chief Data Officer for the Centers for Medicare and Medicaid Services, leading efforts to increase transparency into CMS programs through improved data access and dissemination activities. During her lengthy tenure at the National Center for Health Statistics, she directed the NCHS Data Linkage Program, leading projects designed to integrate federal and state data resources with national survey data to enable innovative analysis of public health and health care systems.

She had both directed and published research on methodologic issues in data linkage, statistical re-identification avoidance strategies, and creation of privacy protected public use data files. During her tenure as Senior Fellow at NORC she has provided expertise to multiple data linkage projects including linkages of national population and health care provider surveys with Medicare, Medicaid, death certificates, U.S. Department of Housing and Urban Development federal housing program participation, and U.S. Department of Veteran’s Affairs data on veteran’s military history and benefit utilization. She has also provided expert advisory services on data disclosure practices to the NCHS and the Social Security Administration (SSA) Data Disclosure Review Boards, the National Death Index and SSA Epidemiologic Verification Service Advisory Boards.

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Expertise

Education

MA

University of Maryland

Honors & Awards

Centers for Disease Control and Prevention Statistical Science Award | 2022

Best Theoretical Paper: “Using synthetic data to replace linkage derived elements: a case study” published in Health Services and Outcomes Research Methodology

Project Contributions

Linking Federal Health Data While Protecting Privacy

Proof that data sets can be combined without exchanging sensitive information

Client:

National Center for Health Statistics (NCHS)

Linking National Hospital Care Survey and CMS Data

Evaluating privacy-preserving linkage techniques and other support

Client:

National Center for Health Statistics

Linking Parent & Statistical Agency Data

Linking NCSES SED and NSF PI data to inform future linkages between a statistical agency and its parent agency

Client:

National Center for Science and Engineering Statistics

National Hospital Care Survey Data Linkages

Linking NHCS data to National Death Index and CMS Master Beneficiary Records

Client:

National Center for Health Statistics (NCHS)

Publications

Research Library & Findings