I think all of the challenges share some concepts in common. It is about law, regulation and coordination of benefit and interest among participated projects/countries.
In any health informatics projects, one way to gain trust from participants and be accepted by professions and academic community including to make the project’s results exchangeable, it is critical for the project owner to take one of the significant privacy compliance frameworks. Currently, there are frameworks that have been enacted, the GDPR in EU and the HIPAA in the U.S. GDPR is not only legislation applies to EU regions but also covering subsidiaries or business unit of organization in the EU. Apart from local law and regulation informatic health project should adopt either of the wide global frameworks to make the project be more acceptable, contributable and ethical concerning personal privacy and rights. Most to concerns about the framework, especially GDPR is that it does not go along with using broad consent. The law prefers participant to be clearly informed about the scope of use of collected data and its result. While at the same time, using dynamic consent may not help facilitate extremely growth in research needs and its possible information exchange. New approaches, combining the two type of consent is needed. The researcher may have to look for broad and possible scope on their project usage in future and how information from the project can be exchanged widely possible. So the researcher can coordinate with possible elaborated projects and organizations to draw a scope and make it written in the consent for future usage. For this vision, application of Entrepreneur Architecture and coordination of benefit and interest between organizations/projects is required for researcher and informatics health project owner. The EA can help speed up using EHR in countries where has less usage in order to join such projects. The EHR will help reduce missing data. Moreover, the coordination between projects and countries will help early assessment of different situation especially in the healthcare setting and society may effect variable required for analysis. The missing data and selection bias can be reduced and improved by training on EHR, data collection and storage, and dissemination among projects/countries. Coordination between projects/countries can help to share infrastructure, software, hardware for data analysis. This, in addition, offers cost containment for joined projects. They can develop core curriculum, procedure and requirement on such shared activities. In the end, integration of the outputs will not be a problem as used to be due to complexity and inadequate variable. The predefined and known variations and lacking some variables among projects help researchers planning an framing of statistical approaches and proper research methodology in advance. The coordination also helps each project/countries improve their project practices, improve health outcome and system in a timely manner.