Questions

Below are questions that the organizers found interesting. Please use these samples as inspiration for the question(s) you want to explore!

In parenthesis, we've provided a link to a suggested dataset that you can use to answer the question. You may also wish to consider other datasets for another perspective or complementary information. For example, you may be able to join two datasets about doctors on their National Provider Identifier (NPI).

Describe the Disorder and Model the Mess

1. Which companies made the most payments? (CMS Open Payments)
2. Which physicians received the most and why? Payment outliers? What is driving the payments? Note: one physician can bill under another and outliers may be misleading; take a look at middle of distribution in addition to outliers
3. Which states received the most? (CMS Open Payments)
4. Total amount paid by type of physician. (CMS Open Payments)
5. How much ownership do physicians have in Manu/GPOs? (CMS Open Payments)
6. How much dollar amount was disputed? Are any physicians/hospitals more likely to dispute than others? Perhaps get a modeling question out of this analysis. (CMS Open Payments)
7. Dollar amount of payments made through third parties. Are any physicians/hospitals more likely to pay through 3rd parties than others? (CMS Open Payments)

Clean the Clutter

1. There really should be two tables, one for recipients that are physicians and one for recipients that are teaching hospitals. (CMS Open Payments)
2. Properly normalize the data, create separate tables for physician info, manu/GPO info, hospital info and pure transaction information. (CMS Open Payments)