Reply To: Focus of Interoperability: EMRs vs Aggregate systems

Homepage Forums Interoperability: Linking RHIS and Other Data Sources Focus of Interoperability: EMRs vs Aggregate systems Reply To: Focus of Interoperability: EMRs vs Aggregate systems

Michael Edwards

I believe that data exchange between existing aggregate systems is not the piece of “cake” that Vikas suggests. If it was, then why don’t we see that it has been done successfully in many of the countries that have implemented aggregate systems? I just haven’t seen it yet. First is the issue of just mapping the facilities between systems. As Dave pointed out, he finds the situation with multiple “master” lists, and I’m sure reconciling these lists hasn’t been done primarily because doing so isn’t that easy, because you probably need to do this manually, as the facility names are probably not standardized, and there is no common unique identifier in use. Large countries have a lot of facilities. For instance, Nigeria has over 30,000 facilities, Tanzania has around 7,000 and Kenya around 10,000. Mapping this many facilities is no piece of cake. Even for a smaller country, there are issues with how facilities are named across different systems. In Haiti, after the 2010 earthquake having a Master Facility List proved indispensable during the rescue, and an international collaboration was brought together to quickly to provide this list. Those efforts are described in this article:

Besides the mapping facilities, you also need to address the issue of mapping fields and indicators. This is not always “a piece of cake” either. For example, when PEPFAR started using DATIM for entry of HIV/AIDS data, there were attempts to set up data exchange between existing systems and national systems. In DATIM, indicators for ART and Counseling and Testing have age and sex breakdowns that are often more detailed than those found in many national systems. DATIM had for Male and Females these age groups: <1, 1-4, 5-9, 10-14, 15-19, 20-24, 24-49, 50+. The national system had only these age groups for males and females: <1, 1-14, 15+. So it was impossible to use data exchange from the national system into DATIM without using calculated percentages, or in other words, making the data up.