Tutorial 1 – Testing Hypotheses and Creating Visualizations with Open Data

In January 8, 2014, Crain’s New York Business published a shocking statistic: the median cost of hip replacements were nearly 10 times higher at New York University Hospitals Center ($103,725) than at Bellevue Hospital Center ($15,436) although they are affiliated institutions and often employ the same surgeons. This report created a lot of publicity about how hospitals set prices and their mark-ups, and how this information can be used to set more appropriate Medicaid reimbursement rates.

Although the report may suggest the existence of uneven practices to estimate mark-ups, it is also possible that legitimate reasons drive –at least in part– these differences. What are some of those plausible reasons? What other factors may have an impact on cost and mark-up? What are important questions to ask about this report?

In this tutorial, we will replicate the Crains’ Report, exploring some hypotheses that you have proposed in the discussion board. As you will see, data analysis is a very iterative process.

Attribution

By Erika Martin and Luis F. Luna-Reyes, and licensed under  CC BY-NC-SA 4.0.

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Data Analytics for Public Policy and Management Copyright © 2022 by Luis F. Luna-Reyes, Erika G. Martin and Mikhail Ivonchyk is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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