Abstract
As for many other scientific domains, public health is nowadays contemplating the opportunities of using but also the challenges of mastering large routinely collected data ('big data') in order to generate knowledge, and to inform and evaluate decisions and policies. In a wide perspective, “public health relevant big data” extends from the “omics” to social network postings.
In this workshop we will concentrate on electronic health records and medical claims data (hereafter referred to as eHRs) which are increasingly being used in public health research and practice. Depending of the national and historical contexts, eHRs encompass details pertaining not only to hospital admissions but also to deaths and infectious diseases registrations, prescriptions and contacts with health services. As a result, eHRs datasets are both long (ie, vast number of records) and wide (i.e., vast amount of information per record). Although the usual public health and epidemiological concepts of inference and causation are still relevant for the analysis of big health data and interpretation of their results, a new set of methodological approaches is also necessary to tackle them. These include for instance quasi-experimental/natural experimental analysis, data mining and machine learning. Recent reviews have demonstrated that these data science terms have corresponding concepts in public health research. This workshop will discuss the use of large routinely collected data in public health with a specific focus on eHRs. The objectives are: to understand the specificity of eHRs in the wider domain of big data; to discuss the challenges imposed when using such data (e.g., data heterogeneity, fragmentation, handling, access, privacy), to discuss how the analysis of big data can assist public health researchers, evaluators and policy-makers; to discuss their advantages and limitations; to outline the methodological, legal and ethical challenges that this entails. Following a brief introduction, the workshop will continue with 5 presentations drawing from a variety of national contexts. The spectrum will spread from countries where eHRs and data linkage have been applied for some years (e.g., Finland, Singapore), to others where development are more recent (France) or even being initiated (Brazil). Together, the presentations will address issues related to the development of big data set, access and training of users and implementation in public health research and practice. The remaining time will be dedicated to interaction with the audience and conclusion.
Key messages
Access and use of big data in the context of public health practice and research is spreading fast. The challenges ahead consist of maintaining and securing vast amount of heterogeneous health and related data, and in building the capacity to analyse them using old and new analytical approaches.
Big Data, Large-Scale Text Analysis, and Public Health Research
