Managing the inevitable trade-offs in population health science practice

2018 ◽  
pp. 133-160
Author(s):  
Sean A. Valles
2017 ◽  
Vol 46 (4) ◽  
pp. 1348-1349
Author(s):  
Glenn Salkeld

2018 ◽  
Vol 2 (11) ◽  
pp. 808-815 ◽  
Author(s):  
Pamela Herd ◽  
Alberto Palloni ◽  
Federico Rey ◽  
Jennifer B. Dowd

Author(s):  
Tarun Reddy Katapally

UNSTRUCTURED Citizen science enables citizens to actively contribute to all aspects of the research process, from conceptualization and data collection, to knowledge translation and evaluation. Citizen science is gradually emerging as a pertinent approach in population health research. Given that citizen science has intrinsic links with community-based research, where participatory action drives the research agenda, these two approaches could be integrated to address complex population health issues. Community-based participatory research has a strong record of application across multiple disciplines and sectors to address health inequities. Citizen science can use the structure of community-based participatory research to take local approaches of problem solving to a global scale, because citizen science emerged through individual environmental activism that is not limited by geography. This synergy has significant implications for population health research if combined with systems science, which can offer theoretical and methodological strength to citizen science and community-based participatory research. Systems science applies a holistic perspective to understand the complex mechanisms underlying causal relationships within and between systems, as it goes beyond linear relationships by utilizing big data–driven advanced computational models. However, to truly integrate citizen science, community-based participatory research, and systems science, it is time to realize the power of ubiquitous digital tools, such as smartphones, for connecting us all and providing big data. Smartphones have the potential to not only create equity by providing a voice to disenfranchised citizens but smartphone-based apps also have the reach and power to source big data to inform policies. An imminent challenge in legitimizing citizen science is minimizing bias, which can be achieved by standardizing methods and enhancing data quality—a rigorous process that requires researchers to collaborate with citizen scientists utilizing the principles of community-based participatory research action. This study advances SMART, an evidence-based framework that integrates citizen science, community-based participatory research, and systems science through ubiquitous tools by addressing core challenges such as citizen engagement, data management, and internet inequity to legitimize this integration.


Author(s):  
Yorghos Apostolopoulos

This chapter contextualizes the volume and describes its organization. It begins by delving into the limitations of the prevailing reductionist paradigm in population health science and the need for a transition from a typically risk factor–based science to a science that recognizes the whole and relationships among parts of pressing population health problems. Next, it walks readers through distinctions between public and population health on the one hand and key concepts of complexity on the other, while offering a shared understanding of population health science and complex systems science. The chapter also lays out the design of and potential audiences for this book.


2016 ◽  
pp. 141-156
Author(s):  
Katherine M. Keyes ◽  
Sandro Galea

2020 ◽  
Vol 4 (s1) ◽  
pp. 132-132
Author(s):  
Tony Kuo ◽  
Moira Inkelas ◽  
Onyebuchi A. Arah ◽  
Vladimir G. Manuel

OBJECTIVES/GOALS: The UCLA Clinical and Translational Science Institute’s Population Health Program is creating versatile scientists who can solve population health problems. This means building learning capability in health care and public health agencies, and fostering a cross-sector, outcomes-based, regional ecosystem for implementation and improvement. METHODS/STUDY POPULATION: A synthesis of achievements and lessons learned reveals the Program’s trajectory. It maps progress in science leading to sustainable interventions for target populations. PHP goals are predicated on networked team science, rather than disorganized assortment of individual studies and interventions, and emphasize design, modeling and iteration. Evolving metrics include network analysis to document collaborative impact; extent of integrating real-world application into systems science and learning system curriculum; legislative and institutional policies developed and adopted; evidence of system orientation, cross-sector focus, and implementation research in scientists’ portfolios; and demonstration of population health impact. Barriers offer the opportunity for iteration and improvement. RESULTS/ANTICIPATED RESULTS: The PHP has progressed in its envisioned shared university-public health stewardship of translation and transformation. Milestones included galvanizing activities such as annual regional dissemination, implementation, and improvement (DII) symposia and Public Health Science Summits; pre- and post-doctoral experiential learning of system science and learning system methods based in Los Angeles County Health Agency initiatives; development of a regional CTSA network for implementation science training; strengthened public health policy practice (e.g., establishing a new Office of Youth Diversion and Development); learning healthcare system capability; and prototypes of population learning systems focused on hypertension, food insecurity, tobacco/vaping, and complex care management. DISCUSSION/SIGNIFICANCE OF IMPACT: PHP is committed to advancing science for population health. Prototypes were an essential initial phase. New areas include use of methodological advances (e.g., artificial intelligence, rapid assessments) in health and public health systems; an academic home for full-time, population-focused clinicians; and social policy innovations.


2010 ◽  
Vol 7 (3) ◽  
pp. 263-283 ◽  
Author(s):  
Kristin Voigt

AbstractThe use of incentives to encourage individuals to adopt ‘healthier’ behaviours is an increasingly popular instrument in health policy. Much of the literature has been critical of ‘negative’ incentives, often due to concerns about equality; ‘positive’ incentives, however, have largely been welcomed as an instrument for the improvement of population health and possibly the reduction of health inequalities. The aim of this paper is to provide a more systematic assessment of the use of incentives from the perspective of equality. The paper begins with an overview of existing and proposed incentive schemes. I then suggest that the distinction between ‘positive’ and ‘negative’ incentives – or ‘carrots’ and ‘sticks’ – is of limited use in distinguishing those incentive schemes that raise concerns of equality from those that do not. The paper assesses incentive schemes with respect to two important considerations of equality: equality of access and equality of outcomes. While our assessment of incentive schemes will, ultimately, depend on various empirical facts, the paper aims to advance the debate by identifying some of the empirical questions we need to ask. The paper concludes by considering a number of trade-offs and caveats relevant to the assessment of incentive schemes.


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