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Distributed data networks: a blueprint for Big Data sharing and healthcare analytics
Author(s) -
Popovic Jennifer R.
Publication year - 2017
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/nyas.13287
Subject(s) - computer science , blueprint , data science , scalability , big data , health care , analytics , data mining , database , engineering , mechanical engineering , economics , economic growth
This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large‐scale, multisite, healthcare‐related distributed data network, the U.S. Food and Drug Administration–sponsored Sentinel Initiative. Analytic infrastructure–development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources.