Analyzing Suspicious Medical Visit Claims from Individual Healthcare Service Providers Using K-Means Clustering

  • Tiago P. HillermanEmail author
  • Rommel N. Carvalho
  • Ana Carla B. Reis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9265)


This study has as its main objective the analysis of healthcare claims data from individual providers, such as independent doctors and allied health professionals, with the purpose of finding excessive billing of medical visitation procedures. We present a discussion of the main difficulties in preventing against abusive claims, and with the use of the CRISP-DM method and the k-means clustering algorithm, propose a model for assessing the behavior of providers engaged in this sort of practice. We conclude that the clustering algorithm was able to provide a more efficient, objective, and reproducible framework for identifying outliers, which could be used for future investigations in similar datasets.


Healthcare Claims Cluster analysis K-means 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Tiago P. Hillerman
    • 1
    Email author
  • Rommel N. Carvalho
    • 2
  • Ana Carla B. Reis
    • 1
  1. 1.University of Brasília – UnB, Campus Universitário Darcy RibeiroBrasíliaBrasil
  2. 2.Department of Research and Strategic Information (DIE)Brazilian Office of the Comptroller General (CGU)BrasíliaBrasil

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