Interesting. This is something that I hoped someone would do. However, I think that for Benford's law to be meaningful, you probably need to be looking at the

Interesting. This is something that I hoped someone would do. However, I think that for Benford's law to be meaningful, you probably need to be looking at the finest-grain stats that are available, not just the top-line national numbers. For instance, to give the U.S. as an example, the national numbers are a sum of state numbers (plus territories), which are themselves in most cases probably a sum of numbers from counties, which are perhaps sums from individual hospitals. For Benford's law to work well I think you have to be looking at the same level where the fake numbers were created. If you add up a whole lot of fake numbers or a combination of real and fake numbers, the frequency distribution of the most significant digit of the total will probably end up being about the same as real data. For example, if fake numbers were being generated at the state level in four states, and at the county level in 30 different counties, and at 20 hospitals, then the national numbers would probably still look fine. If we don't know whether fake data might be injected at the national, state, or county level or from individual hospitals then we'd have to check all of them. And if the data at the granularity we need to be looking at just isn't available then we probably won't be able to detect it just by applying Benford's law.