Desafios à privacidade dos dados na área da saúdea interoperabilidade no domínio da segurança Challenges to data privacy in healthinteroperability in the field of security

Hierarchical Bayesian regression models, with differing hyper-prior distributions, are considered as accident prediction models to be fitted on data collected over several years on the Portuguese motorway network. A sensitivity analysis is performed by way of simulation to investigate the practical implications of the choice of informative hyper-priors (Gamma, Christiansen and Uniform) and non-informative Gamma, as well as various sample sizes and years of aggregated data, on the results of a road safety analysis, in particular, at detecting high accident risk locations. It was concluded that informative hyper-priors were best at detecting hotspots when small sample sizes were considered. For bigger samples the various hyper-priors produced equivalent outcomes. Furthermore, more accurate results were obtained when more years of data were analyzed.

Data sharing between organizations through interoperability initiatives involving multiple information systems is fundamental to promote the collaboration and integration of services. However, in terms of data, the considerable increase in its exposure to additional risks, require a special attention to issues related to privacy of these data.For the Portuguese healthcare sector, where the sharing of health data is, nowadays, a reality at national level, data privacy is a central issue, which needs solutions according to the agreed level of interoperability between organizations. This context led the authors to study the factors with influence on data privacy in a context of interoperability, through a qualitative and interpretative research, based on the method of case study.This article presents the final results of the research that successfully identifies 10 subdomains of factors with influence on data privacy, which should be the basis for the development of a joint protection program, targeted at issues associated with data privacy.