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      Informatics Metrics and Measures for a Smart Public Health Systems Approach: Information Science Perspective

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          Abstract

          Public health informatics is an evolving domain in which practices constantly change to meet the demands of a highly complex public health and healthcare delivery system. Given the emergence of various concepts, such as learning health systems, smart health systems, and adaptive complex health systems, health informatics professionals would benefit from a common set of measures and capabilities to inform our modeling, measuring, and managing of health system “smartness.” Here, we introduce the concepts of organizational complexity, problem/issue complexity, and situational awareness as three codependent drivers of smart public health systems characteristics. We also propose seven smart public health systems measures and capabilities that are important in a public health informatics professional's toolkit.

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          Achieving a nationwide learning health system.

          We outline the fundamental properties of a highly participatory rapid learning system that can be developed in part from meaningful use of electronic health records (EHRs). Future widespread adoption of EHRs will make increasing amounts of medical information available in computable form. Secured and trusted use of these data, beyond their original purpose of supporting the health care of individual patients, can speed the progression of knowledge from the laboratory bench to the patient's bedside and provide a cornerstone for health care reform.
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            Complex systems thinking and current impasses in health disparities research.

            Complex systems approaches have received increasing attention in public health because reductionist approaches yield limited insights in the context of dynamic systems. Most discussions have been highly abstract. There is a need to consider the application of complex systems approaches to specific research questions. I review the features of population health problems for which complex systems approaches are most likely to yield new insights, and discuss possible applications of complex systems to health disparities research. I provide illustrative examples of how complex systems approaches may help address unanswered and persistent questions regarding genetic factors, life course processes, place effects, and the impact of upstream policies. The concepts and methods of complex systems may help researchers move beyond current impasse points in health disparities research.
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              Making Sense of Sensemaking 1: Alternative Perspectives

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                Author and article information

                Journal
                Comput Math Methods Med
                Comput Math Methods Med
                CMMM
                Computational and Mathematical Methods in Medicine
                Hindawi Publishing Corporation
                1748-670X
                1748-6718
                2017
                10 January 2017
                : 2017
                : 1452415
                Affiliations
                1The Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 1101-C McGavran-Greenberg Bldg., CB 7411, Chapel Hill, NC 27599-7411, USA
                2The Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 1101-F McGavran-Greenberg Bldg., CB # 7411, Chapel Hill, NC 27599-7411, USA
                Author notes
                *Timothy Jay Carney: tcarney@ 123456unc.edu

                Academic Editor: Alejandro Rodríguez-González

                Author information
                http://orcid.org/0000-0002-2152-9478
                Article
                10.1155/2017/1452415
                5259665
                15c04804-d040-403a-97aa-9905956a6f06
                Copyright © 2017 T. J. Carney and C. M. Shea.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 September 2016
                : 30 November 2016
                : 4 December 2016
                Funding
                Funded by: University of North Carolina
                Funded by: Gillings School of Public Health
                Funded by: Lineberger Comprehensive Cancer Center
                Funded by: Carolina Community Network Center to Reduce Cancer Health Disparities Diversity Supplement
                Award ID: 3U54CA153602
                Categories
                Review Article

                Applied mathematics
                Applied mathematics

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