Lung cancer analysis of factors influencing hospital costs

Abstract

Health care costs for the control reference reveal the cost of lung cancer patient factors. Hospital cost data have many complex factors in both quantitative and qualitative variables. The use of traditional multiple regression analysis is not appropriate. This study uses BP neural network modeling and sensitivity analysis of factors analysis. In this paper, lung cancer patient factors affecting the cost of BP neural network modeling, through sensitivity analysis found the main factors followed by days of hospitalization, treatment outcome, age, hospital number, occupation, cost categories, admissions, etc., and proposed to shorten the hospital stay time for a breakthrough by the medical insurance system reform, strengthening the role of the medical cost control system to solve. © 2012 Springer Science+Business Media B.V.