Articlehybrid2023

Big Data in Oncology Nursing Research: State of the Science

Carolyn Harris · Rachel A. Pozzar · Yvette P. Conley · Manuela Eicher · Marilyn J. Hammer · Kord M. Kober +2 more

16 citations0/0 files storedSeminars in Oncology Nursing

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Big Data Technologies and Applications Artificial Intelligence in Healthcare and Education Artificial Intelligence in Healthcare

Abstract

OBJECTIVE: To review the state of oncology nursing science as it pertains to big data. The authors aim to define and characterize big data, describe key considerations for accessing and analyzing big data, provide examples of analyses of big data in oncology nursing science, and highlight ethical considerations related to the collection and analysis of big data. DATA SOURCES: Peer-reviewed articles published by investigators specializing in oncology, nursing, and related disciplines. CONCLUSION: Big data is defined as data that are high in volume, velocity, and variety. To date, oncology nurse scientists have used big data to predict patient outcomes from clinician notes, identify distinct symptom phenotypes, and identify predictors of chemotherapy toxicity, among other applications. Although the emergence of big data and advances in computational methods provide new and exciting opportunities to advance oncology nursing science, several challenges are associated with accessing and using big data. Data security, research participant privacy, and the underrepresentation of minoritized individuals in big data are important concerns. IMPLICATIONS FOR NURSING PRACTICE: With their unique focus on the interplay between the whole person, the environment, and health, nurses bring an indispensable perspective to the interpretation and application of big data research findings. Given the increasing ubiquity of passive data collection, all nurses should be taught the definition, characteristics, applications, and limitations of big data. Nurses who are trained in big data and advanced computational methods will be poised to contribute to guidelines and policies that preserve the rights of human research participants.

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2013A New Dimension of Health Care: Systematic Review of the Uses, Benefits, and Limitations of Social Media for Health Communication 2019Big data in healthcare: management, analysis and future prospects 2018Big Data Analytics in Medicine and Healthcare 2020Threats of Bots and Other Bad Actors to Data Quality Following Research Participant Recruitment Through Social Media: Cross-Sectional Questionnaire 2016The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches 2015Nursing Needs Big Data and Big Data Needs Nursing 2020Latent bias and the implementation of artificial intelligence in medicine 2018Ethical Issues in Social Media Research for Public Health

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