On Sunday September 25 2011, a one-day training event on “Measuring Health Equity and Financial Protection using ADePT” was conducted at the University of Cartagena, Columbia, as part of the 6th International Conference of the International Society for Equity in Health.
What did the training cover?
The one-day course provided training in the quantitative methods used to measure equity and financial protection in the health sector. Sessions included:
- Measuring inequality in health outcomes and health care utilization - the concentration curve and concentration index
- Benefit-incidence analysis
- Financial protection – catastrophic and impoverishing health care payments
- Measuring equity in health care financing – progressivity analysis
Each session commenced with a presentation of concepts and methodology by the instructors. Then, participants got hands-on experience in using the ADePT software to carry out the techniques on their own laptops using datasets drawn from the LSMS, DHS and WHS surveys. The World Bank team provided participants with flash drives containing the software, purposively-created mini-datasets and other training materials. The training was conducted by a team consisting of Adam Wagstaff, Daniela Hoshino and Emiliana Gunawan from the World Bank, together with logistical and technical support from staff of the University of Cali.
What did participants in Cartagena say?
Participants, who hailed mainly from Latin America, rated the event highly. 95% of participants rated “overall training quality” as a 4 or 5 on a 5-point scale, around 85% reported an “improvement in skills as a result of the training” as 4 or 5, and 95% rated “performance of instructors in managing the event” as 4 or 5. As before, feedback from the evaluations will be used to further improve the training course and the ADePT software.
“Great session! I know I still have a lot to learn, but I now have great resources and know where to start.”
“Despite a few bugs in the software, ADePT is clearly a useful tool to produce evidence to inform policy makers, provided you have reliable and clean datasets. Perhaps it should have an additional module to help users handle dirty datasets.”
“Follow-up training should be scaled up in order to internalize lessons learnt.”
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