Studies from Shandong University Update Current Data on Internet and World Wide Web (Medical Treatment Migration Behavior Prediction and Recommendation Based On Health Insurance Data)

2020 JUN 22 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Researchers detail new data in Internet and World Wide Web. According to news reporting originating in Jinan, People’s Republic of China, by NewsRx journalists, research stated, “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 news reporters obtained a quote from the research from Shandong University, “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.”

According to the news reporters, the research concluded: “Finally, the experiment demonstrates that the model proposed in this paper is more accurate than other models.”

For more information on this research see: Medical Treatment Migration Behavior Prediction and Recommendation Based On Health Insurance Data. World Wide Web, 2020;23(3):2023-2042. World Wide Web can be contacted at: Springer, One New York Plaza, Suite 4600, New York, Ny, United States. (Springer - www.springer.com; World Wide Web - http://www.springerlink.com/content/1386-145x/)

Our news correspondents report that additional information may be obtained by contacting Y.L. Shi, Shandong University, School of Software, Jinan, People’s Republic of China. Additional authors for this research include L. Cheng and K. Zhang.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1007/s11280-020-00781-3. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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