Research on the application of data mining technology in clinical medicine
The 21st century is a highly informatized era, with the rapid development of computer information technology and the need for the construction of hospital informatization platforms, more and more software companies have designed and developed a variety of medical management systems to meet the needs of various hospitals.
Abstract This paper firstly starts from the basic concept of data mining technology, analyzes the characteristics of clinical medical data, discusses the application of data mining technology in the field of clinical medicine, and puts forward an outlook on its application and development of clinical medicine in the future.
Keywords data mining; clinical medicine; medical system; application
I. Introduction
General hospitals above the county and municipal level, with the introduction of paperless office systems in hospitals, the hospitals rely on the healthcare information management system is becoming more and more intense, using the more and more information management systems, resulting in more and more complex hospital management.
However, with the accumulation of time, each hospital information management system stores a large amount of data resources, including text, sound, images, video, images and other medical data, the traditional simple data query has been gradually unable to meet the needs of hospital managers
. How to extract data from a large amount of medical data that is beneficial to the service of clinical practice and leadership management decision-making is particularly important, and the use of data mining technology in this regard should be born. Therefore, to improve the utilization of these information resources, through more effective analysis, integration and utilization of these data, can better provide comprehensive, accurate and timely decision-making basis for patients, medical staff, researchers and management personnel, is today's medical and health care industry urgently need to solve the problem.
Second, the concept of data mining technology
Data mining (DataMining), also translated as data exploration, it refers to a large number of incomplete, fuzzy variety of data from the extraction of hidden, not found, but the existence of valuable information in the exploration process. It is a technique to find its law from a large amount of data by analyzing each data, which mainly has 3 steps of data preparation, law finding and law representation.
Data mining is usually associated with computer science, and achieves these goals through many methods such as statistics, online analytical processing, intelligence retrieval, machine learning, expert systems (relying on past rules of thumb), and pattern recognition. Its basic idea is to extract from various data valuable . information with the aim of helping decision makers to find potential connections between data and discover overlooked elements from it, which are useful for predicting and deciding behavior.
The steps of data mining will vary with the applications in different domains, and each data mining technique will have its own characteristics and steps to be used, and there will be differences in the data mining processes developed for different problems and needs. In addition, the completeness of the data, the degree of professional support, etc. will have an impact on the establishment of the data mining process. These factors contribute to the variability of the use, planning, and processes of data mining in different fields, and even within the same industry, the degree of involvement of analytical techniques and expertise varies, making the systematization and standardization of the data mining process particularly important.
Characteristics of clinical medical data
1. Data diversity. Clinical medical data are thousands, including text, sound, pictures, symbols, images, videos, etc., so there are many types of structure, which is its most significant feature. As data exploration and discovery is more difficult, making the development of a generalized medical data software system more complex.
2. Huge amount of data. With the continuous improvement of people's living standards, more and more people put their health in the first place, from time to time to the hospital to do the experience, the hospital a variety of medical equipment will produce thousands of medical data information, ultimately leading to rapid growth in the amount of medical data.
3. Data characterization is not significant. Medical data has text, graphics and other non-numerical data, making it difficult for data miners to find the correspondence between data. Different doctors have different levels of medical skills, and there may be uncertainty in diagnosing the patient's condition during the diagnosis and treatment process, leading to incomplete diagnosis and difficulty in discovering accurate information, which ultimately leads to a large amount of the same or similar data being generated every day, resulting in a large amount of redundancy in medical data.
4. Data standards are not standardized. In the medical world, there is no unified standardized criteria for naming many medicines. For example, a simple Chinese medicine has many aliases, such as lotus, alias Lotus, June Flower God, Water Chihuahua, Water Rue, Lotus Root Flower, Water Hibiscus, Monarch Flower, and Tien Hsien Flower, and so on.
5. Importance of data security. Patients in the hospital after the completion of treatment will leave a variety of medical data, a lot of data is the patient's privacy, hospital administrators in the data analysis and resource **** enjoyment, to ensure the security of the data to prevent leakage of patient privacy.
Four, the application of data mining technology in the field of clinical medicine
1. Application in medical diagnosis With the upgrading of China's hospital information technology platform construction, various large hospitals are investing in the construction of information technology platforms, and gradually adopting the electronic medical record system that is suitable for their own hospitals and realizing the information **** enjoyment within the hospital. When the doctors of different departments are analyzing the data, they can correspond the results of various tests and examinations of different patients with various disease conditions, and establish a detailed medical diagnosis data warehouse, according to which the doctors can carry out rapid and accurate diagnosis, thus effectively improving the diagnostic efficiency of the doctors. At the same time, it can also accurately record the number of patients of different age groups with different types of diseases, which is convenient for hospital administrators to analyze and study the data statistically in the future.
2. With the continuous reform of the national health insurance policy, the proportion of hospitalized patients using health insurance for reimbursement of expenses is increasing year by year. Due to various reasons, the health insurance system is separated from urban and rural areas, how to help hospital managers quickly and accurately grasp the cost of health insurance patients and the proportion of out-of-pocket expenses is an important task for the management of hospitals. Using data mining technology to create data interfaces between the hospital information system and various types of medical insurance, establish a comparison table of drugs, materials, diagnostic and therapeutic items, etc., and create a module for transmitting medical prescriptions and costs to realize the uploading and downloading of medical data from various hospitals, so as to facilitate real-time auditing, supervision and management of medical insurance patients by the medical insurance department and the hospital administrators and to reasonably control their medical costs.
3. The application of hospital management through the collection, collation, analysis and mining of various hospital medical data, the hospital can form a complete data analysis report, which can provide hospital managers with high-quality medical data results, and play an important role in decision-making hospital management, controlling medical costs, grasping the medical costs, analyzing the economic benefits, and improving the quality of medical services. For example, by analyzing patient waiting time and consultation, we can optimize the outpatient consultation process and make corresponding adjustments to the configuration of healthcare personnel, thus improving the efficiency of the hospital and better serving the patients.
4. The application of medical scientific research is also an important part of the hospital's work, for example, by organizing and analyzing historical case data, researchers can form a high-quality medical research paper; through the study and research of genetic engineering, researchers can use scientific methods to effectively predict the future, so as to obtain a new variety of new products, and produce new products.
V. Future Prospects
Medicine, the discipline of dealing with various diseases or lesions of the human body through scientific or technological means, is a special specialty, which has a certain degree of specificity and complexity, and various hospitals should choose the clinical medical data analysis and mining tools suitable for them when building the hospital information technology platform. Make full use of the key technology of data mining, the correct collection, analysis and mining of clinical medical data, as large as possible to play it in the acquisition of medical information in the maximum value, so as to better serve the medical cause, for the work of the hospital, and ultimately allow more patients to benefit for life!
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