scholarly journals The intersection of genomics and big data with public health: Opportunities for precision public health

PLoS Medicine ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. e1003373
Author(s):  
Muin J. Khoury ◽  
Gregory L. Armstrong ◽  
Rebecca E. Bunnell ◽  
Juliana Cyril ◽  
Michael F. Iademarco
Keyword(s):  
Public Health ◽  
Big Data ◽  
Precision Public Health

scholarly journals Beyond Public Health Genomics: Can Big Data and Predictive Analytics Deliver Precision Public Health?

2018 ◽  
Vol 21 (5-6) ◽  
pp. 244-250 ◽  
Author(s):  
Muin J. Khoury ◽  
Michael Engelgau ◽  
David A. Chambers ◽  
George A. Mensah
Keyword(s):  
Public Health ◽  
Big Data ◽  
Predictive Analytics ◽  
Public Health Genomics ◽  
Precision Public Health

scholarly journals Convergence of Precision Medicine and Public Health Into Precision Public Health: Toward a Big Data Perspective

2021 ◽  
Vol 9 ◽  
Author(s):  
Pedro Elkind Velmovitsky ◽  
Tatiana Bevilacqua ◽  
Paulo Alencar ◽  
Donald Cowan ◽  
Plinio Pelegrini Morita
Keyword(s):  
Public Health ◽  
Big Data ◽  
Precision Medicine ◽  
Health Data ◽  
Use Cases ◽  
The Other ◽  
Data Types ◽  
Holistic View ◽  
Precision Public Health ◽  
Other Hand

The field of precision medicine explores disease treatments by looking at genetic, socio-environmental, and clinical factors, thus trying to provide a holistic view of a person's health. Public health, on the other hand, is focused on improving the health of populations through preventive strategies and timely interventions. With recent advances in technology, we are able to collect, analyze and store for the first-time large volumes of real-time, diverse and continuous health data. Typically, the field of precision medicine deals with a huge amount of data from few individuals; public health, on the other hand, deals with limited data from a population. With the coming of Big Data, the fields of precision medicine and public health are converging into precision public health, the study of biological and genetic factors supported by large amounts of population data. In this paper, we explore through a comprehensive review the data types and use cases found in precision medicine and public health. We also discuss how these data types and use cases can converge toward precision public health, as well as challenges and opportunities provided by research and analyses of health data.

scholarly journals Scientific challenges for precision public health

2020 ◽  
Vol 74 (4) ◽  
pp. 311-314 ◽  
Author(s):  
Frank Kee ◽  
David Taylor-Robinson
Keyword(s):  
Public Health ◽  
Big Data ◽  
Intervention Strategy ◽  
Current Theory ◽  
Individual Agency ◽  
Precision Public Health ◽  
New Information ◽  
The Social ◽  
The Subject ◽  
Scientific Questions

The notion of ‘precision’ public health has been the subject of much debate, with recent articles coming to its defence following the publication of several papers questioning its value.Critics of precision public health raise the following problems and questionable assumptions: the inherent limits of prediction for individuals; the limits of approaches to prevention that rely on individual agency, in particular the potential for these approaches to widen inequalities; the undue emphasis on the supposed new information contained in individuals’ molecules and their ‘big data’ at the expense of their own preferences for a particular intervention strategy and the diversion of resources and attention from the social determinants of health.In order to refocus some of these criticisms of precision public health as scientific questions, this article outlines some of the challenges when defining risk for individuals; the limitations of current theory and study design for precision public health; and the potential for unintended harms.

scholarly journals Big data hurdles in precision medicine and precision public health

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Mattia Prosperi ◽  
Jae S. Min ◽  
Jiang Bian ◽  
François Modave
Keyword(s):  
Public Health ◽  
Big Data ◽  
Precision Medicine ◽  
Precision Public Health

Navigating the Ethics of Big Data in Public Health

2019 ◽  
pp. 353-367
Author(s):  
Effy Vayena ◽  
Lawrence Madoff
Keyword(s):  
Public Health ◽  
Big Data ◽  
Credit Card ◽  
Health Sector ◽  
Public Health Research ◽  
Ethical Challenges ◽  
The Public ◽  
Health Community ◽  
Digital Disease Detection ◽  
The Public Sphere

“Big data,” which encompasses massive amounts of information from both within the health sector (such as electronic health records) and outside the health sector (social media, search queries, cell phone metadata, credit card expenditures), is increasingly envisioned as a rich source to inform public health research and practice. This chapter examines the enormous range of sources, the highly varied nature of these data, and the differing motivations for their collection, which together challenge the public health community in ethically mining and exploiting big data. Ethical challenges revolve around the blurring of three previously clearer boundaries: between personal health data and nonhealth data; between the private and the public sphere in the online world; and, finally, between the powers and responsibilities of state and nonstate actors in relation to big data. Considerations include the implications for privacy, control and sharing of data, fair distribution of benefits and burdens, civic empowerment, accountability, and digital disease detection.

scholarly journals 4.C. Round table: Joining forces: frameworks for international and multi-sectoral collaborations in health information

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
◽  
Keyword(s):  
Public Health ◽  
Big Data ◽  
Health Information ◽  
Population Health ◽  
Round Table ◽  
Secondary Use ◽  
Use Of Data ◽  
National Initiatives ◽  
Information Research

Abstract Countries have a wide range of lifestyles, environmental exposures and different health(care) systems providing a large natural experiment to be investigated. Through pan-European comparative studies, underlying determinants of population health can be explored and provide rich new insights into the dynamics of population health and care such as the safety, quality, effectiveness and costs of interventions. Additionally, in the big data era, secondary use of data has become one of the major cornerstones of digital transformation for health systems improvement. Several countries are reviewing governance models and regulatory framework for data reuse. Precision medicine and public health intelligence share the same population-based approach, as such, aligning secondary use of data initiatives will increase cost-efficiency of the data conversion value chain by ensuring that different stakeholders needs are accounted for since the beginning. At EU level, the European Commission has been raising awareness of the need to create adequate data ecosystems for innovative use of big data for health, specially ensuring responsible development and deployment of data science and artificial intelligence technologies in the medical and public health sectors. To this end, the Joint Action on Health Information (InfAct) is setting up the Distributed Infrastructure on Population Health (DIPoH). DIPoH provides a framework for international and multi-sectoral collaborations in health information. More specifically, DIPoH facilitates the sharing of research methods, data and results through participation of countries and already existing research networks. DIPoH's efforts include harmonization and interoperability, strengthening of the research capacity in MSs and providing European and worldwide perspectives to national data. In order to be embedded in the health information landscape, DIPoH aims to interact with existing (inter)national initiatives to identify common interfaces, to avoid duplication of the work and establish a sustainable long-term health information research infrastructure. In this workshop, InfAct lays down DIPoH's core elements in coherence with national and European initiatives and actors i.e. To-Reach, eHAction, the French Health Data Hub and ECHO. Pitch presentations on DIPoH and its national nodes will set the scene. In the format of a round table, possible collaborations with existing initiatives at (inter)national level will be debated with the audience. Synergies will be sought, reflections on community needs will be made and expectations on services will be discussed. The workshop will increase the knowledge of delegates around the latest health information infrastructure and initiatives that strive for better public health and health systems in countries. The workshop also serves as a capacity building activity to promote cooperation between initiatives and actors in the field. Key messages DIPoH an infrastructure aiming to interact with existing (inter)national initiatives to identify common interfaces, avoid duplication and enable a long-term health information research infrastructure. National nodes can improve coordination, communication and cooperation between health information stakeholders in a country, potentially reducing overlap and duplication of research and field-work.

scholarly journals The academic viewpoint on Big data and patient data ownership (as seen in the scientific literature)

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
I Mircheva ◽  
M Mirchev
Keyword(s):  
Public Health ◽  
Big Data ◽  
Medical Research ◽  
Information And Communication Technologies ◽  
Patient Information ◽  
Scientific Literature ◽  
Medical Data ◽  
Patient Data ◽  
Academic Community ◽  
Ethical Challenges

Abstract Background Ownership of patient information in the context of Big Data is a relatively new problem, apparently not yet fully understood. There are not enough publications on the subject. Since the topic is interdisciplinary, incorporating legal, ethical, medical and aspects of information and communication technologies, a slightly more sophisticated analysis of the issue is needed. Aim To determine how the medical academic community perceives the issue of ownership of patient information in the context of Big Data. Methods Literature search for full text publications, indexed in PubMed, Springer, ScienceDirect and Scopus identified only 27 appropriate articles authored by academicians and corresponding to three focus areas: problem (ownership); area (healthcare); context (Big Data). Three major aspects were studied: scientific area of publications, aspects and academicians' perception of ownership in the context of Big Data. Results Publications are in the period 2014 - 2019, 37% published in health and medical informatics journals, 30% in medicine and public health, 19% in law and ethics; 78% authored by American and British academicians, highly cited. The majority (63%) are in the area of scientific research - clinical studies, access and use of patient data for medical research, secondary use of medical data, ethical challenges to Big data in healthcare. The majority (70%) of the publications discuss ownership in ethical and legal aspects and 67% see ownership as a challenge mostly to medical research, access control, ethics, politics and business. Conclusions Ownership of medical data is seen first and foremost as a challenge. Addressing this challenge requires the combined efforts of politicians, lawyers, ethicists, computer and medical professionals, as well as academicians, sharing these efforts, experiences and suggestions. However, this issue is neglected in the scientific literature. Publishing may help in open debates and adequate policy solutions. Key messages Ownership of patient information in the context of Big Data is a problem that should not be marginalized but needs a comprehensive attitude, consideration and combined efforts from all stakeholders. Overcoming the challenge of ownership may help in improving healthcare services, medical and public health research and the health of the population as a whole.

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