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Expectations and boundaries for Big Data approaches in social medicine.

Dimeglio, Chloé; Kelly-Irving, Michelle; Lang, Thierry; Delpierre, Cyrille.
J Forensic Leg Med; 57: 51-54, 2018 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-29801952
It seems no longer possible to produce knowledge, even biological knowledge regardless of social, cultural and economic environments in which they were observed. Therefore never the term "social medicine" or more generally "social biology" has appeared more appropriate. This way of linking the social and the biological exceeds the sole social medicine by involving also other medical disciplines. As such, forensics, whose an important activity is represented by clinical forensics in charge of types of violence (physical, psychological, sexual, abuse) and persons held in custody could see its practice heavily modified through the use of various data describing both the clinical situation of patients but also their context of life. A better understanding of mechanisms of violence development and potentially a better prevention of these situations allow forensics not to be restricted (or seen as limited to) a "descriptive medicine", but to be seen also as a preventive and curative medicine. In this evolution, the potential contribution of Big Data appears significant insofar as information on a wide range of characteristics of the environment or context of life (social, economic, cultural) can be collected and be connected with health data, for example to develop models on social determinants of health. In the common thinking, the use of a larger amount of data and consequently a multiplicity of information via a multiplicity of databases would allow to access to a greater objectivity of a reality that we are approaching by fragmented viewpoints otherwise. In this light, the "bigger" and "more varied" would serve the "better" or at least the "more true". But to be able to consider together or to link different databases it will be necessary to know how to handle this diversity regarding hypotheses made to build databases and regarding their purposes (by whom, for what bases have been made). It will be equally important to question the representativeness of situations that led to the creation of a database and to question the validity of information and data according to the secondary or tertiary uses anticipated from their original purpose. This step of data validity control for the anticipated use is a sine qua non condition, particularly in the field of public health, to guarantee a sufficient level of quality and exploit in the best way the benefits of Big Data approaches.
Selo DaSilva