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基于神经网络和支持向量机的手术治疗乳腺癌患者住院费用影响因素分析。

Analysis of Influencing Factors on Hospitalization Expenses of Patients with Breast Malignant Tumor Undergoing Surgery: Based on the Neural Network and Support Vector Machine.

机构信息

West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China.

West China School of Medicine, Sichuan University, Chengdu 610041, Sichuan, China.

出版信息

J Healthc Eng. 2021 Nov 24;2021:9268660. doi: 10.1155/2021/9268660. eCollection 2021.

Abstract

OBJECTIVE

Analyze the influencing factors of hospitalization expenses of breast cancer patients in a tertiary hospital in Chengdu and provide a basis and suggestion for controlling the unreasonable increase of medical expenses.

METHODS

The first pages of all inpatient medical records of patients with breast malignant tumor from 2017 to 2020 were extracted, and the descriptive analysis, single-factor analysis, and multifactor analysis were conducted by using the statistical method and data mining method to explore the influencing factors of hospitalization expenses.

RESULTS

In 2017-2020, the average hospitalization cost and the average surgical treatment cost increased year by year, and the number of operations, actual hospitalization days, and CCI were the important influencing factors.

CONCLUSION

It is suggested to strengthen the supervision of medical rationality and eliminate the waste of medical resources; and we should improve the efficiency of diagnosis and treatment services, so as to shorten the actual length of hospitalization; at the same time, the combination of DRG grouping and fine management can be used to control the hospitalization expenses.

摘要

目的

分析成都市某三甲医院乳腺癌患者住院费用的影响因素,为控制医疗费用不合理增长提供依据和建议。

方法

提取 2017-2020 年所有乳腺恶性肿瘤住院患者病案首页信息,采用统计学方法和数据挖掘方法进行描述性分析、单因素分析和多因素分析,探讨住院费用的影响因素。

结果

2017-2020 年,平均住院费用和平均手术治疗费用逐年增加,手术例数、实际住院天数、CCI 是重要的影响因素。

结论

建议加强医疗合理性监管,消除医疗资源浪费;提高诊疗服务效率,缩短实际住院天数;同时可采用 DRG 分组与精细化管理相结合的方式控制住院费用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f2/8635896/1a617a986753/JHE2021-9268660.001.jpg

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