The value of Complex Networks in Healthcare Insurance Data

LUIS G. MOYANO; ANA PAULA APPEL; MÁRCIA ITO; VAGNER FIGUEREDO DE SANTANA; CLAUDIO PINHANEZ

Torino

Conferencia; Challenges in Data Science: A Complex System Perspective; 2015

Kyoto University

We present a data science take on large Healthcare claim database from one of the largest Brazilian insurance companies. We applied complex network methods to find a set of 'best' doctors through metrics, some examples of which are: temporality, reciprocity and ?loyalty?. Networks are defined by relationships, as most data is. Network-derived insights are usually not reachable from other analyses. As a consequence, complex networks methods may be vary valuable to data science.