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Public Health Informatics and the Public Health Workforce in an Era of Change

2014; Elsevier BV; Volume: 47; Issue: 5 Linguagem: Inglês

10.1016/j.amepre.2014.07.014

1873-2607

Martin Sepulveda,

Ethics in Clinical Research

The velocity of societal change is unprecedented and is affecting both the developed and developing worlds. Transformations are being driven by numerous forces, including information and technology, capital flows, competition for economic development, demographic shifts, natural resources, climate, and conflict. Major change is occurring in all societal sectors and at all levels, including individual, community, and enterprise. At the individual and enterprise levels, for example, mobile and wireless digital devices with handheld communication and computing capability have redefined business, education, and social behaviors and processes. Rapid changes are also occurring at the community infrastructure level. In China, for example, high-speed rail systems twice the length of European and Japanese railway systems with a reservation system larger than the total of all airlines worldwide have been built in less than 7 years.1Stone M. China: high-speed rail network to be doubled. http://news.sky.com/story/1194709/china-high-speed-rail-network-to-be-doubled.Google Scholar Such changes are transforming government, business, work, and the professions, and are generating massive quantities of new digital data in all sectors, including those with particular relevance to the determination of health.2McKinsey Global Institute. Big data: the next frontier for innovation, competition, and productivity. mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation.Google Scholar The following viewpoint regarding transformations in societies and change for public health professionals is framed by this context of exponential high-velocity change, data, and information explosion. It is a compilation of messages presented at the 2014 Public Health Informatics Conference and the 2014 Alexander Langmuir Lecture, Epidemic Intelligence Service Conference. Four forces for change are examined in the following three sections and their relevance to the work of these professionals is discussed. Healthcare delivery system reform in the U.S. has been spurred by unaffordable costs and provisions of the Affordable Care Act 2010. New models of care have been launched such as medical homes in primary care, health homes with extended services in communities, and accountable care organizations in hospital or multispecialty group systems. Early short-term outcomes from these new models are mixed but generally supportive of better value from reduced hospital and emergency department use and improved delivery of preventive care.3Patient-Centered Primary Care Collaborative. Summary of patient-centered medical home cost and quality results, 2010–2013. Washington DC: Patient-Centered Primary Care Collaborative, 2013. www.pcpcc.net/sites/default/files/PCPCC%20Medical%20Home%20Cost%20and%20Quality%202013.pdf.Google Scholar, 4Salmon R.B. Sanderson M.I. Walters B.A. Kennedy K. Flores R.C. Muney A.M. A collaborative accountable care model in three practices showed promising early results on costs and quality of care.Health Aff. 2012; 31: 2379-2387Crossref Scopus (30) Google Scholar Despite the pressing need for better approaches to care delivery, there is a gross imbalance in the large expenditures for care delivery compared to jobs, education, housing, transport, food, and other real determinants of health.5IOMFor the public's health: the role of measurement in action and accountability. National Academies Press, Washington DC2010Google Scholar Investing in community transformation for better health is not yet a core strategy for solving our health crisis. The inability of population health professionals to make the investment case for community transformations has been due in part to the unavailability of data from these sectors and the technologies, skills, and systems to use them. Novel partnerships to exploit data repositories and assets of other enterprises in pursuit of shared problems have also been slow to develop. One such example is the Orange S.A. Data 4 Development project,6Orange S.A. Data 4 Development Initiative. orange.com/en/content/view/full/11624.Google Scholar which challenged researchers to use its massive mobile subscriber data in the Ivory Coast to improve population well-being. Creative use of these data by public and private research laboratories delivered actionable insights such as improving tourist experience through geospatial analyses, generating useful economic development indices with poverty and mobility patterns, improving safety and preventing violence during events, and improving privacy of open data sets. Cities have become the locus of the world's population and play an increasingly vital role in total population health strategies. More than half of the developed world's population became urban in the 1950s, and the developing world will achieve this before the year 2020. In 2009, more than half the world's population lived in cities, with growth rates highest in low- and middle-income countries in non-Japan Asia and Sub-Saharan Africa.7WHO. World Urbanization Prospects, the 2011 Revision. http://esa.un.org/unup/pdf/FINAL-FINAL_REPORT%20WUP2011_Annextables_01Aug2012_Final.pdf.Google Scholar Cities attract people for economic opportunity and social reasons. Cities provide employment, concentrate capital, afford better leverage of infrastructure, and contain the talent and business sector networks to exploit and extend innovation. Conversely, cities can create and scale socioeconomic disparities, crime, and violence, and disseminate diseases and behavioral patterns that constrain opportunity, health, and equity. Population growth in cities is challenging governments to transform services and operations to serve their populations and create sustainable environments that drive human and economic development. The need to improve the speed, integration, unit cost, transparency, and effectiveness of city operations is acute, and data and information are being used to drive these changes. For example, water systems are being instrumented, interconnected, and analyzed for quality, leakage, utilization, contamination, and predictive maintenance. The traffic and transportation sector is using data collection and analytics for assessing citizen mobility, fleet optimization, traffic, event and parking management, and forecasting.8IBM Institute for Business ValueA vision of smarter cities. IBM, Armonk NY2009http://www-03.ibm.com/press/attachments/IBV_Smarter_Cities_-_Final.pdfGoogle Scholar Digitization of legacy data systems and data from sensors and objects in these and other sectors relevant to health provide opportunities for public health professionals to help solve municipal problems in ways that also benefit population health. Public health professionals will need to invest time in these efforts and acquire data and systems literacy in these domains. Two additional forces for change with relevance for public health professionals such as public health practitioners, informaticians, and epidemiologists are big data and cognitive computing. Instrumented objects, pervasive sensors throughout our environments, and personal devices capture video, voice, image, and other data forms of very large size very quickly. It is estimated that the worldwide digital universe will double every 2 years to 40 trillion gigabytes (40 zeta bytes) by 2020, which is equivalent to more than 5,200 gigabytes for every person on earth.9International Data Corporation. The digital universe in 2020. http://www.emc.com/collateral/analyst-reports/idc-the-digital-universe-in-2020.pdf.Google Scholar In addition, objects, devices, systems, and services are all becoming web aware or connected in an Internet of Things estimated to reach 1 trillion by 2015.10Höller J. Tsiatsis V. Mulligan C. Karnouskos S. Avesand S. Boyle D. From machine-to-machine to the Internet of things: introduction to a new age of intelligence. Elsevier, Amsterdam2014Google Scholar This unprecedented level of quantification offers the potential to redefine public health systems from surveillance to planning, research, mobilization and response, and assessment and forecasting. It also creates the potential for insight and intervention among the social and environmental determinants of health at a population level with systems science methods such as modeling and simulation.11Maglio P. Sepulveda M.-J. Mabry P. Mainstreaming modeling and simulation to accelerate public health innovation.Am J Public Health. 2014; 104: 1181-1186Crossref PubMed Scopus (30) Google Scholar Cognitive computing is ushering in a new era where machines perform cognitive functions such as memory, learning, judgment, and inference. This is being made possible by combining many scientific methods and tools like natural language processing, algorithmic mathematics, optimization, and machine learning. People can interact with these advanced cognitive computer systems through normal speech and receive decision support that provides feedback with probabilities attached based on the quality of the evidence.12Kelly III, J.E. Hamm S. Smart machines: IBM's Watson and the era of cognitive computing. Columbia Business School Press, New York2014Google Scholar These systems have enormous application in public health when work involves synthesizing and evaluating large volumes or rapidly developing information on complex problems involving unstructured data such as outbreaks, exposures, syndromes, or syndemics. The public health workforce faces complicated but not insurmountable barriers for advantaging data generation, technology, and societal transformations to advance total population health. Some are technical, such as data standards and systems interoperability; some are professional, such as workforce, skills, and practices; some are legal and regulatory, such as access, privacy, and confidentiality; and some are due to funding and work process. Overcoming these challenges will require profession-driven re-skilling in multi-sectoral data literacy, systems science methods, and the relentless pursuit of innovative partnerships. Publication of this article was supported by the U.S. Centers for Disease Control and Prevention (CDC), an Agency of the Department of Health and Human Services, under the Cooperative Agreement with the Public Health Foundation and University of Michigan Center of Excellence in Public Health Workforce Studies (CDC RFA-OT13-1302). The ideas expressed in the articles are those of the authors and do not necessarily reflect the official position of CDC. No other financial disclosures were reported by the author of this paper.