Cluster analysis and its application to healthcare claims data: a study of end-stage renal disease patients who initiated hemodialysis

2016120 citationsJournal Articlegold Open Access

Authors

Minlei Liao · LEK Consulting (United States)

Yunfeng Li · Health Outcomes Solutions (United States)

Farid Kianifard · Tris Pharma (United States)

N Engels · Rutgers, The State University of New Jersey

Stephen Arcona · Health Outcomes Solutions (United States)

Abstract

The K-means CA method appeared to be the most appropriate in healthcare claims data with highly skewed cost information when taking into account both change of cost patterns and sample size in the smallest cluster.

Topics & Keywords

Artificial Intelligence in Healthcare Statistical Methods and Inference Advanced Statistical Process Monitoring

Publication Details

Published in: BMC Nephrology

Volume 17, Issue 1, pp. 25-25

DOI: 10.1186/s12882-016-0238-2

Field-Weighted Citation Impact: 19.54

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Cluster analysis and its application to healthcare claims data: a study of end-stage renal disease patients who initiated hemodialysis

Authors

Abstract

Topics & Keywords

Publication Details