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I was discussing #healthcare cost variation (& #EHP #RBP models) across geography with a colleague earlier today. I have followed the work of @zackcooperYale and thought it would be interesting to, in very simple terms, visualize some of the cost variation. A short thread. 1/n
2/n I started looking for a datasource. While our #benefitconsulting and #insurance clients engage networks of private insurers, that data is subject to different rules... I wondered what variation "looks like" for Medicare claims. I landed here: dartmouthatlas.org
3/n First, there is a ton of #Medicare data. It can be downloaded by state (see below) as well as to a county level (which I pulled into Python.) To consider the amount of cost attributable to different segments, I looked at the largest categories with observations by county. 
