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J. health inform ; 8(supl.I): 309-318, 2016. ilus, tab, graf
Article in Portuguese | LILACS | ID: biblio-906276

ABSTRACT

O objetivo é analisar os relacionamentos entre médicos que possuem pacientes em comum a partir de sinistros de seguradora de saúde. Utilizou-se a técnica de analítica de grafos para modelar os relacionamentos e foram calculadas métricas de centralidades para encontrar a importância relativa dos médicos. Houve a concordância das métricas de grau e auto valor e de betweenness e closeness (10% a 15% no top 100 médicos). Além disso, os 5 médicos com maior valor na métrica de auto valor estão altamente conectados entre si. Conclui-se que as métricas captaram o relacionamento entre os médicos desta comunidade que coincidem com a literatura indicando que é possível encontrar médicos que colaboram entre si no cuidado do paciente dentro e fora do hospital. Além disso, os médicos de maior auto valor indicam que são referência para outros médicos e médicos que estão conectados com muitos outros sugerem que estes influenciam nas decisões de seus pacientes.


The aim of this work is to analyze the relationship between physicians from a health insurance company,who attend the same patient. We use graph analytics to model the physician's relationship. Centrality metrics were calculated to find the relative importance of the physicians. There was the agreement on the metrics of degree and eingenvalue and of betweenness and closeness (10% to 15% in the top 100 physicians). In addition, physicians with5 highest eigenvalue in the metric are highly interconnected. We conclude that the metrics captured the relations hipbetween the physicians in this community that coincide with the literature, indicating that we can find physicians who collaborate on patient care within and outside the hospital. In addition, physicians with largest eigenvalue indicate thatthey are reference to other physicians, and physicians who are connected to many others, suggest, that they influence their patients' decisions.


Subject(s)
Humans , Data Mining , Interprofessional Relations , Congresses as Topic , Insurance, Health
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