Predictive reliability and validity of hospital cost analysis with dynamic neural network and genetic algorithm
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ORIGINAL ARTICLE
Predictive reliability and validity of hospital cost analysis with dynamic neural network and genetic algorithm Le Hoang Son1 Pham Van Hai5
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Angelo Ciaramella2 • Duong Thi Thu3 • Antonino Staiano2 • Tran Manh Tuan4
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Received: 27 December 2018 / Accepted: 20 March 2020 Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Hospital cost analysis (HCA) becomes a key topic and forefront of politics, social welfare and medical discourse. HCA includes a wide range of expenses; yet the foremost attention relates to the money expense in which hospital managers would like to draw a figure of incomes in the past and future. Based on the HCA results, they can develop many plans for improving hospital’s service quality and investing in potential healthcare services in order to deliver better services with lower costs. Machine learning methods are often opted for prediction in HCA. In this paper, we propose a new method for HCA that uses genetic algorithm (GA) and artificial neural network (ANN). Operators of GA are used to boost up calculation to get optimal weights in the forward propagation of ANN. Experiments on a real database of Hanoi Medical University Hospital (HMUH) including calculus of kidney and ureter inpatients show that the new method achieves better accuracy than the relevant ones including linear regression, K-nearest neighbors (KNN), ANN and deep learning. The mean squared error of the proposed model gets the lowest value (0.00360), compared to those of deep learning, KNN and linear regression which are 0.00901, 0.01205 and 0.01718 respectively. Keywords Hospital cost analysis Medical informatics Artificial neural networks Genetic algorithm Strategic management
& Le Hoang Son [email protected] Angelo Ciaramella [email protected] Duong Thi Thu [email protected] Antonino Staiano [email protected] Tran Manh Tuan [email protected] Pham Van Hai [email protected] 1
VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam
2
Department Science and Technology, University of Naples Parthenope, Naples, Italy
3
Hanoi Medical University, Hanoi, Vietnam
4
Thuyloi University, Hanoi, Vietnam
5
School of Information and Communication Technology, Hanoi University of Science and Technology, Hanoi, Vietnam
1 Introduction In the modern world, since the expense for healthcare services becomes high, hospitals need to thoroughly evaluate the relation between the number of patients and the total hospital cost [23, 39]. Based on the achieved results, hospital managers can formulate different plans to improve quality of healthcare services and adjust investment to potential strategies. Hospital cost analysis (HCA) has become a crucial topic and forefront of political, social welfare and medical discourse [31, 36]. In USA, hospital revenues and expenses per admission increased roughly 5% per year from 2000 to 2009 [36]. Health insurance covered either a part of or the whole c
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