Our goal is to create a Master Person Index (MPI) that unambiguously identifies each individual who receives health care in the State of Utah. This index will enable qualified clinical and translational research to be performed in an environment with unique attributes: (1) over 80% of all patient care in the State is supplied by three providers, and these encounters (ambulatory and in-patient) are recorded electronically;and (2) extensive experience unmatched in other states of creating a research infrastructure (the Utah Population Database) that provides a demographic and familial description for much of the population of Utah and that is linked to corresponding medical data. We propose to create the technology and policies for a statewide MPI in order to satisfy the critical need to link records across disparate institutions. Each MPI entry will contain only enough information to uniquely identify an individual and map that individual to original data sources. While the MPI will not contain encounter-specific information, it will provide the capability for qualified investigators to link institutional records into patient-specific longitudinal health histories. The outcome of this proposal will be a unique research infrastructure but with strategies and methodologies that can be adopted as a model for other institutions. Its impact would have broad relevance to a variety of research interests supported by NIH Institutes and Centers. To address the challenge of securely and confidentially linking records across disparate institutions, we will establish a statewide Master Person Index that includes a master repository (database) of demographic information from the contributing institutions, and the services surrounding the repository to allow authorized access. We will establish guidelines to ensure institutions the ability to contribute to, use, and safeguard the statewide MPI. We will investigate and implement methods for matching and merging records. We will demonstrate the ability of health care and public health institutions to add new records to the MPI, update existing records, and query the repository for links to corresponding person-records at other institutions. We will utilize the State's health information exchange infrastructure to prove extensibility of the system to the statewide environment. We will develop a governance and financing model that will ensure the long-term viability of the statewide MPI. The outcome of this proposal will be a unique research infrastructure but with strategies and methodologies that can be adopted as a model for other institutions.

Public Health Relevance

A statewide MPI will satisfy the critical need to link records across disparate institutions in order to provide the capability for qualified investigators, clinicians and public health officials to link institutional records into patient- specific longitudinal health histories. The development of this critical resource will have a significant statewide impact on the entire population of the Utah for research, clinical and public health outcomes. We also anticipate a national impact because of our goal to provide MPI guidelines and methodologies that could be adopted by other states and regions, and because use of the MPI will facilitate studies with broader applicability of research results.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
High Impact Research and Research Infrastructure Programs (RC2)
Project #
5RC2LM010798-02
Application #
7940821
Study Section
Special Emphasis Panel (ZRG1-HDM-E (99))
Program Officer
Vanbiervliet, Alan
Project Start
2009-09-30
Project End
2013-09-29
Budget Start
2010-09-30
Budget End
2013-09-29
Support Year
2
Fiscal Year
2010
Total Cost
$1,500,701
Indirect Cost
Name
University of Utah
Department
Miscellaneous
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Bradford, Wayne; Hurdle, John F; LaSalle, Bernie et al. (2014) Development of a HIPAA-compliant environment for translational research data and analytics. J Am Med Inform Assoc 21:185-9
He, Shan; Hurdle, John F; Botkin, Jeffrey R et al. (2010) Integrating a Federated Healthcare Data Query Platform With Electronic IRB Information Systems. AMIA Annu Symp Proc 2010:291-5