Health care analytics: análise de reincidência e modelagem preditiva para detecção de futuros pacientes de alto custo no sistema de saúde brasileiro
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2016-05-31
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Santos, Rafael Chaves
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Healthcare sector analyses have proven that a small portion of individuals with chronic conditions consume the majority of the resources needed for the treatment of these conditions. Therefore, to achieve the industry’s primary objectives of providing healthcare, reducing costs and improving the patients’ overall wellness, the Brazilian healthcare system should employ proactive models of intervention regarding patients who are very likely to become high-cost. Approaches focusing on specific populations and data quality allow decision makers to have a clear comprehension of the needs presented by each specific group - groups are established as per industry practice - and to plan actions oriented toward cost reduction and improved quality of the services provided. This study aims to assess a risk modelling strategy for predicting which specific types of patients are likely to become high-cost individuals in the Brazilian healthcare system. Such modeling is comprised by Health Analytics Strategies that characterize the global insurance industry and seeks to identify potentially high-cost patients by using data mining techniques, historical data and predictive analysis.