OBJECTIVES: To describe big data and data science in the context of oncology nursing care. DATA SOURCES: Peer-reviewed and lay publications. CONCLUSION: The rapid expansion of real-world evidence from sources such as the electronic health record, genomic sequencing, administrative claims and other data sources has outstripped the ability of clinicians and researchers to manually review and analyze it. To promote high-quality, high-value cancer care, big data platforms must be constructed from standardized data sources to support extraction of meaningful, comparable insights. IMPLICATIONS FOR NURSING PRACTICE: Nurses must advocate for the use of standardized vocabularies and common data elements that represent terms and concepts that are meaningful to patient care.
OBJECTIVES: To describe big data and data science in the context of oncology nursing care. DATA SOURCES: Peer-reviewed and lay publications. CONCLUSION: The rapid expansion of real-world evidence from sources such as the electronic health record, genomic sequencing, administrative claims and other data sources has outstripped the ability of clinicians and researchers to manually review and analyze it. To promote high-quality, high-value cancer care, big data platforms must be constructed from standardized data sources to support extraction of meaningful, comparable insights. IMPLICATIONS FOR NURSING PRACTICE: Nurses must advocate for the use of standardized vocabularies and common data elements that represent terms and concepts that are meaningful to patient care.