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Abstract:
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The American healthcare system constitutes 18% of GDP, or $3 Trillion. That means "big data".
In particular, healthcare related organizations have a wide range of data-related tasks, including measurement development, data gathering, analyses, and reporting. The result is different databases and analytic systems may have been built, primarily for reporting. However, these databases are not necessarily linked in a manner that easily enables analyses of relationships between factors that influence healthcare delivery. An example is analyzing relationships between nursing, clinical quality and patient experience.
In this case study, we describe a system to centralize and utilize data from different databases. This system covers the spectrum of "Data Science" responsibilities and include 1) a centralized database with a well-organized schema, 2) analytic tools (e.g. SAS, R, Tableau, PowerBI) and 3) a modularized process and code library for producing automated reports. The result is a "one stop shop" where the data scientist can spend more time doing what we love - answering questions and sharing findings - and less time data engineering and manually producing reports.
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