HOSPITAL MEDICAL BEHAVIOUR SUPERVISION AND OPERATIONAL EFFICIENCY EVALUATION METHOD BASED BASED ON BIG DATA PLATFORM

被引：0
作者：
LIU Y.I. [1 ]
ZHANG Y.I. [1 ]
机构：
[1] Department of Medical Technology, Chongqing Medical and Pharmaceutical College, Chongqing
来源：
Scalable Computing | 2024年 / 25卷 / 03期
关键词：
Big Data; Efficiency Evaluation; Medical Behavior;
D O I：
10.12694/SCPE.V25I3.2764
中图分类号：
学科分类号：
摘要：
The application of cloud computing and big data core technologies and concepts to medical informatization can improve its flexibility and efficiency, and achieve the overall deployment and intensive management of the system. In the era of big data, the use of information management platform can optimize and standardize clinical diagnosis and treatment process, improve the quality and efficiency of diagnosis and treatment services, and improve the quality and level of scientific research, which meets the requirements of medical reform for fine management of hospitals and precise medical treatment in the era of evidence-based medicine. This paper introduces the development and application of big data analysis in the field of information technology. Through the research on the supervision of hospital medical service behavior, the top-level design is used to standardize the content of medical behavior supervision, and the effectiveness of supervision is discussed to achieve the purpose of reducing clinical paperwork. Based on the needs, the medical service behavior supervision system is proposed and constructed. Strengthen hospital medical behavior supervision through hospital big data analysis and knowledge base system support. This system can provide management with an effective monitoring and management tool, enabling them to promptly identify and solve problems that arise in medical services. By analyzing a large amount of medical data, hospitals can help predict the trend of disease occurrence in advance, thereby taking preventive and control measures in advance, and reducing the occurrence and spread of diseases. Through deep learning and analysis of patient data, personalized treatment plans can be provided for each patient to improve treatment effectiveness. © 2024 SCPE.
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页码：1852 / 1862
页数：10
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