Open AccessHealthcare data safe havens: towards a logical architecture and experiment automation
Author(s) -
Robertson David,
Giunchiglia Fausto,
Pavis Stephen,
Turra Ettore,
Bella Gabor,
Elliot Elizabeth,
Morris Andrew,
Atkinson Malcolm,
McAllister Gordon,
Manataki Areti,
Papapanagiotou Petros,
Parsons Mark
Publication year - 2016
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2016.0170
Subject(s) - data sharing , architecture , jurisdiction , computer science , health care , data science , computer security , work (physics) , risk analysis (engineering) , engineering , business , medicine , law , political science , mechanical engineering , art , alternative medicine , pathology , visual arts
In computing science, much attention has been paid to generic methods for sharing data in secure infrastructures. These sorts of methods and infrastructures are, of course, necessary for sharing healthcare data. The authors are, however, a long way away from being able to realise the potential of medical and healthcare data to support the sorts of extensive, data‐intensive experiments being demanded by precision and stratified medicine. A key architectural problem remaining to be solved is how to maintain control of patient data within the governance of local data jurisdictions, while also allowing these jurisdictions to engage with experiment designs that (because of the need to scale to large population sizes) may require analyses across several jurisdictions. This study provides a snapshot of architectural work underway to provide a clear, effective structure of data safe havens within jurisdictions. It then describes how formally specified experiment designs can be used to enable jurisdictions to work together on experiments that no single jurisdiction could tackle alone. The authors’ current work relates to two jurisdictions (in Scotland and in Italy), but the architecture and methods are general across similar jurisdictions.