Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management

201581 citationsJournal Articlegreen Open Access

Authors

Michael J. Hassett · Harvard University

Hajime Uno · Dana-Farber Cancer Institute

Angel M. Cronin · Dana-Farber Cancer Institute

Nikki M. Carroll · Kaiser Permanente

Mark C. Hornbrook · Kaiser Permanente Center for Health Research

Debra P. Ritzwoller · Kaiser Permanente

Abstract

Valid and reliable detection of recurrence using big data is feasible. These tools will enable extensive, novel research on quality, effectiveness, and outcomes for lung and colorectal cancer patients and those who develop recurrence.

Topics & Keywords

Global Cancer Incidence and Screening Machine Learning in Healthcare Data Quality and Management

Publication Details

Published in: Medical Care

Volume 55, Issue 12, pp. e88-e98

DOI: 10.1097/mlr.0000000000000404

Field-Weighted Citation Impact: 0.86

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Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management

Authors

Abstract

Topics & Keywords

Publication Details