Andrew Nguyen - Hands-On Healthcare Data: Taming the Complexity of Real-World Data

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This will be the 1st chapter of the final book. The GitHub repo for this book is available at https://gitlab.com/andrew-nguyen/hands-on-healthcare-data.

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Healthcare data is an exciting vertical for data science and there are manyopportunities to have real impact, whether from a clinical or technicalperspective. For patients and clinicians, there is the alluring promise oftruly personalized care where patients gets the right treatment at the righttime, tailored to their genetics, environment, beliefs, and lifestyleeachrequiring the effect integration, harmonization, and analysis of highly complexdata. For data scientists and computer scientists, there are many openproblems for natural language processing, graphs, semantic web, and databases,among many others.

Additionally, there are also frontier problems that arise given the specificcombination of a specific technology and the nuances and complexities ofhealthcare. For example, there is nothing about healthcare data itself nordata science that requires regulatory grade reproducibility. Data scientistsknow how to use version control tools such as Git and IT people know how tocreate database snapshots and use Docker containers. However, regulatorybodies such as the US Food and Drug Administration (FDA) or the EuropeanMedicines Agency (EMA), there are specific requirements to track and storemetadata and other artifacts to prove the results of the analysis, includingreproducibility. Similarly, there is increasing desire and pressure to ensurereproducibility of studies or the sharing of negative results among academics.How we can address these challenges at scale is still unsolved.