I was privileged to be able to attend the SciBraai/Code4SA/ICFJ DataQuest event this past Saturday. A simple but effective formula – put a bunch of techies, data scientists and journalists in a room, ply them with coffee and a great braai, and give them free reign on all the data you have – then see what they come up with.
The entire initiative is very inspiring. Code for South Africa has made it their mission to drive data-driven journalism, and the event made it clear that there are stories in our data that the rest of us need to see.
My personal favorite was a project about our dams and water supply in the western cape, visibly illustrating where our water comes from – and it’s not what you think. It was also an eye-opener to learn how far our water supplies have dwindled since last year: the equivalent of 51x the volume of the Cape Town Stadium.
My project took on the healthcare angle. I teamed up with a data scientist who prefers to fly under the radar, and Bibi-Aisha, an eNCA reporter. We made use of the South African Hospitals Survey 2011-2012 data (link) – it was produced by a survey initiative several years ago, and is pretty comprehensive, covering public healthcare facilities right across South Africa.
Comprehensive, and sobering.
The survey data tracked performance on several points – how often the hospitals were open, how many people were on staff, the leadership and governance, infrastructure, and so on. The facilities were largely self-rated, and a summary “Overall Performance” percentage was calculated for each one.
As far as we could see (and based on the report’s own standards), any hospital scoring 80% or above in the Overall Performance score was well-run. We split the remainder at 0-40% for red, and 41-79% for yellow. The first thing that hit us clear over the head was that only 16% of the facilities in this survey actually passed Government standards.
Of course, the obvious caveat: This data is 3 years old, and things have changed in healthcare since then. Personally I don’t think they could have changed that much, though, given the myriad other issues the Government has had to deal with over the last 3 years.
But there was something else surprising – we started finding outliers. Clinics and hospitals in remote areas, suffering the same issues as their neighbours, and yet were able to report higher scores despite that:
I think there’s a story there. For whatever reason, these facilities are performing better, and they might have lessons to share with the rest of us about how they’re doing it.
- Source Data: Hosted by Code4SA
- Map Tool: http://lab.wogan.me/sa-hospitals-map/
- Map Tool Source: On GitHub
- Presentation: On SlideShare
If you build/clone/enhance/report on any of this, I’d love to hear about it!