Don’t overreact to this. It’s really not a big deal. I have worked with data of this kind for years. First of all, there are a bunch of datasets like this o

Don’t overreact to this. It’s really not a big deal. I have worked with data of this kind for years. First of all, there are a bunch of datasets like this or very similar to it both public and private. Example: have you ever been to a hospital in California? There is a state agency called OSHPD which makes inpatient discharge records available to academic researchers (like me) and to others like insurers. Texas, Oklahoma, New York (iirc) and many many other states make similar data sources available. What’s actually in the data? Generally all of the ICD-9 or -10 codes generated by a visit. There may be very limited demographic information - race, ethnicity, zip code, age. That’s about it. (That’s what de-identified means here.) Sometimes it will tell you the source of admission (eg “arrived by ambulance”), and generally will tell you the source of the payment (eg “patient has private insurance”). Some of these datasets will let you track patients over time (TX has a version like that) within a year. It is extremely extremely difficult to match this information to actual people, assuming anyone even cared to do so (which almost certainly no one does!). For one thing, most zip codes are large and contain many people (generally only three digits of the zip are reported if there are very few records from that zip). More importantly, you just don’t have that much information about anyone in the data - you would have a row which essentially says: “Hispanic male age 50-54 from zip code 78201 who was billed for a knee replacement.” Good luck figuring out who that is! Even for very rare illnesses it doesn’t work… if you already knew someone in 78201 had X Rare Disease and went to Y hospital, you might be able to find the record in the data with some work. But what additional information would you get? Maybe how much his insurance was billed?? You already had to know the guy had a rare disease just to find him! Also - observe the fact that this dataset keeps getting sold. That tells you something about how useful it actually is in practice. I get that some MBA at IBM thought it would be great for “generating insights” about cost drivers and saving money. It’s really not. If you look for the “cost drivers” in this data you will see that long visits and complicated procedures are costly. And then your next step is…??? This data does not give you anything which will help you predict or avert such episodes. Neither IBM nor anyone else has actually come remotely close to solving this problem, right? I am not aware of a single effort which has even moved the needle on spending by 1%! After holding on to it for a few years, IBM or whoever owns it next will talk up its value and sell it to another sucker. (If it were really worth that much to IBM, they wouldn’t sell it!) If you want proof that there isn’t a privacy concern here, get exactly this data from Texas (which makes it publicly available). Open it up and let me know how easy a time you have finding anyone you can identify. Even if you have friends and family in the state who you know went to the hospital you’re going to have an extremely hard time.