Study Findings on Managed Care Are Outlined in Reports from Northeastern University (An Abnormal Surgical Record Recognition Model With Keywords Combination Patterns Based On Textrank for Medical Insurance Fraud Detection): Managed Care

Health Policy and Law Daily

2023 MAY 01 (NewsRx) -- By a News Reporter-Staff News Editor at Health Policy and Law Daily -- Fresh data on Managed Care are presented in a new report. According to news originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “Increasing insurance fraud has resulted in the loss of large amounts of money, making it difficult to expand insurance coverage and scale. This phenomenon is particularly acute in the field of health insurance.”

Funders for this research include Fundamental Research Funds for the Central Universities, National Key R&D Program of China, Shenyang Medical Imaging Processing Engineering Technology Research Center.

Our news journalists obtained a quote from the research from Northeastern University, “Medical insurance fraud is the falsification of medical records to obtain medical insurance funds or medical insurance benefits. Therefore, effective detection of health insurance fraud is of great importance for the rational use of health insurance funds. To address the frequent violations and frauds in health insurance, this paper proposes a keyword combination-based approach for health insurance fraud detection. First, a medical dictionary is built by TextRank to segment the surgical procedure text and extract the surgical keywords, then, the synonyms corresponding to each keyword are extracted from the electronic medical record data to form a keyword combination pattern as the final detection rule, and finally, a medical insurance fraud detection model is built on this basis. In this paper, data on acute myocardial infarction and unstable angina were selected for examination, with 1371 and 1787 cases, respectively. The performance of the model was evaluated by the coverage rate and compared experimentally with the TF-IDF and LDA algorithms. The experiments also prove the efficiency and advancedness of the algorithm in this paper. In the case of acute myocardial infarction, the method in this paper improved the coverage rate by 23.77% and 9.4% compared with the TF-IDF and LDA methods respectively.”

According to the news editors, the research concluded: “In the case of unstable angina, the coverage of the method in this paper was improved by 20.21% compared to both TF-IDF and LDA methods.”

This research has been peer-reviewed.

For more information on this research see: An Abnormal Surgical Record Recognition Model With Keywords Combination Patterns Based On Textrank for Medical Insurance Fraud Detection. Multimedia Tools and Applications, 2023. Multimedia Tools and Applications can be contacted at: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands. (Springer - www.springer.com; Multimedia Tools and Applications - http://www.springerlink.com/content/1380-7501/)

The news correspondents report that additional information may be obtained from Xin Min, Northeastern University, School of Computing Science and Engineering, Shenyang, People’s Republic of China. Additional authors for this research include Wei Li, Panpan Ye, Weidong Xie and Kun Yu.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1007/s11042-023-14529-4. 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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