Abstract
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 language | English (US) |
|---|---|
| Title of host publication | Nursing and Informatics for the 21st Century - Embracing a Digital World, 3rd Edition, Book 3 |
| Subtitle of host publication | Innovation, Technology, and Applied Informatics for Nurses |
| Publisher | Taylor and Francis |
| Pages | 81-94 |
| Number of pages | 14 |
| ISBN (Electronic) | 9781000573497 |
| ISBN (Print) | 9781032249810 |
| DOIs | |
| State | Published - Jan 1 2022 |
Bibliographical note
Publisher Copyright:© 2022 selection and editorial matter, Connie White Delaney, Charlotte A. Weaver, Joyce Sensmeier, Lisiane Pruinelli & Patrick Weber.