An Informatics Framework to Support Surveillance System Interoperability in Minnesota

How to Cite

Patnoe, S., LaVenture, M., Johnson, R. E., Fritz, J., Frohnert, B., Mbinda, G., Soderberg, K., & Allen, B. (2017). An Informatics Framework to Support Surveillance System Interoperability in Minnesota. Online Journal of Public Health Informatics, 9(1).


ObjectiveTo create an informatics framework and provide guidanceto help Minnesota’s public health surveillance systems achieveinteroperability and transition to standards-based electronicinformation exchange with external health care providers using thestate’s birth defects registry as an initial pilot program.IntroductionThe Minnesota Department of Health (MDH) needs to be ableto collect, use, and share clinical, individual-level health dataelectronically in secure and standardized ways in order to optimizesurveillance capabilities, support public health goals, and ensureproper follow-up and action to public health threats. MDH programs,public health departments, and health care providers across the stateare facing increasing demands to receive and submit electronic healthdata through approaches that are secure, coordinated, and efficient;use appropriate data standards; meet state and federal privacy laws;and align with best practices. This framework builds upon existinginformatics models and two past studies assessing health informationexchange (HIE) conducted by the MDH Office of Health InformationTechnology (OHIT) to provide MDH surveillance systems with anoutline of the key elements and considerations for transitioning tomore secure, standards-based, electronic data exchange.MethodsDevelopment of the informatics framework incorporatesinformation gathered in several phases. The first phase involvesadditional analysis of data collected from the MDH InformaticsAssessment of Interoperability and HIE1that was conducted in 2015to evaluate the current state of interoperability and HIE readinessacross the agency. The second phase involves a comprehensiveenvironmental scan and literature review of existing standards,practices, models, toolkits, and other resources related to electronicHIE and interoperability. The third phase involves gathering additionalinformation on programmatic needs, workflows, and capabilitiesthrough key informant interviews. Key informants include programmanagers, staff, and content-area experts from select MDH programs,the state’s central information technology organization (MN.IT), andexternal health care provider organizations including hospitals.Minnesota’s birth defects registry, the Birth Defects InformationSystem (BDIS), was selected as the pilot program because it wasidentified in the 2015 MDH Informatics Assessment as having a highlevel of interest in implementing an interoperable and standards-driven approach to electronic health data exchange. The BDIS is alsoexploring options for being designated as an eligible public healthregistry for Meaningful Use. As a pilot program for this project,the BDIS assists in the development and implementation of theinformatics framework.ResultsThe 2015 MDH Informatics Assessment identified and evaluated21 MDH programs with information systems that accept and manageclinical, individual-level health information. Among these 21 MDHprograms, wide variations exist regarding information system size(range, 400 to 10,000,000 individuals), staffing numbers (range, 0.2 to21 FTEs), budgets (range, $20,000 to $1,876,000), and other keycharacteristics. Despite these variations, programs identified similarbarriers and needs related to achieving interoperability and electronicHIE. Areas of need include management and information technologysupport to make interoperability a priority; policies and governance;additional application functionality to support HIE; and additionalskills for the workforce. Results from the environmental scan and keyinformant interviews will be incorporated with additional analyses ofthe 2015 MDH Informatics Assessment to inform the development ofan agency-wide informatics framework to support MDH programs inachieving interoperability.ConclusionsMDH surveillance systems are calling for practical guidance tohelp implement and maintain a more efficient and effective wayto electronically collect, use, and share health data with externaland internal stakeholders. This informatics framework provides anoutline of the key elements and considerations for achieving greaterinteroperability across MDH surveillance systems. Additionalresearch is required to assess how system interoperability and HIEcan improve data quality and advance population health goals.
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