Applied Data Science

Lisiane Pruinelli, Maxim Topaz

Research output: Chapter in Book/Report/Conference proceedingChapter


Data science has a broad definition, including all the processes needed to extract meaning from big data for a specific knowledge domain. A better understanding of data science concepts and skillsets is needed to move this discipline forward, including concepts and resources available to conduct real-world analytics projects that have the potential to improve health outcomes. Although several conceptual frameworks have been used and adapted from various specialties to support data science, a small number are focused on healthcare data. Additionally, these frameworks are not widely adopted nor are they readily available to stakeholders, including researchers, clinicians and the general public. In this chapter, the Applied Healthcare Data Science Roadmap is presented, which is a framework aiming to educate healthcare leaders on the use of data science principles and tools to inform decision-making. Several use cases will illustrate the application of data science for healthcare outcomes.

Original languageEnglish (US)
Title of host publicationNursing and Informatics for the 21st Century - Embracing a Digital World, 3rd Edition, Book 3
Subtitle of host publicationInnovation, Technology, and Applied Informatics for Nurses
PublisherTaylor and Francis
Number of pages14
ISBN (Electronic)9781000573497
ISBN (Print)9781032249810
StatePublished - Jan 1 2022

Bibliographical note

Publisher Copyright:
© 2022 selection and editorial matter, Connie White Delaney, Charlotte A. Weaver, Joyce Sensmeier, Lisiane Pruinelli & Patrick Weber.


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