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Medical treatment migration behavior prediction and recommendation based on health insurance data

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Abstract

How to accurately predict the future medical treatment behaviors of patients from the historical health insurance data has become an important research issue in healthcare. In this paper, an Attention-based Bidirectional Gated Recurrent Unit (AB-GRU) medical treatment migration prediction model is proposed to predict which hospital patients will go to in the future. The model considers the impact of medical visit on the future medical behavior, on the basis of Bidirectional Gated Recurrent Unit (B-GRU) framework, we introduce an attention mechanism to determine the strength of hidden state at different moments, which can improve the predictive performance of the model. Due to medical treatment in different places has an important impact on the distribution of health insurance funds, the individual patient would be expected to the appropriate hospital and get the appropriate medical treatment. Therefore, when medical treatment prediction has been completed, this paper proposes a Similarity and Double-layer CNN-based (SD_CNN) medical treatment migration recommendation model. The model introduces a CNN framework to achieve patient similarity learning, and compares similarities to recommend whether patients need medical treatment migration. Finally, the experiment demonstrates that the model proposed in this paper is more accurate than other models.

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Acknowledgements

This work was supported by the National Key Research and Development Plan of China (No.2018YFC0114709), the Natural Science Foundation of Shandong Province of China for Major Basic Research Projects (No.ZR2017ZB0419), the Taishan Industrial Experts Program of Shandong Province of China (No.tscy20150305).

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Authors and Affiliations

  1. School of Software, Shandong University, Jinan, China

    Lin Cheng, Yuliang Shi & Kun Zhang

  2. Dareway Software Co., Ltd, Jinan, China

    Yuliang Shi & Kun Zhang

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  1. Lin Cheng
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  2. Yuliang Shi
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Correspondence to Yuliang Shi.

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Guest Editors: Jie Shao, Man Lung Yiu, and Toyoda Masashi

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Cheng, L., Shi, Y. & Zhang, K. Medical treatment migration behavior prediction and recommendation based on health insurance data. World Wide Web 23, 2023–2042 (2020). https://doi.org/10.1007/s11280-020-00781-3

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