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Many efforts have been made to improve data collection in developing countries. Health Management Information Systems (HMIS) and their overall weak performance in providing reliable data are crucial considerations for health systems in these settings. This talk by PhD candidate Grégoire Lurton reflects on ways to improve HMIS data usage, focusing on data management and data analysis innovations.

Based on current research at IHME and at the University of Washington’s Computer Science and Engineering department’s Data Science Incubator, two examples of HMIS data leveraging will be presented: how metadata from Excel spreadsheets have been used to compile and standardize batches of reports from Kenyan HMIS, and how data from Open Street Map can be matched with HMIS data from Nigeria to estimate geo-localization of health services.

Finally, Lurton will discuss how the increasing availability of structured HMIS data changes the way information and decision-making should be linked. Using Alain Desrosières’ typology of the use of statistics for policymaking, he will propose the possibility of a Learning State as being most adapted to the data available through HMIS.