Since the computerization of medical records, the hospital has accumulated more than one million people's outpatient and hospitalization records. However, these valuable medical big data have not been fully integrated and applied. The hospital took the lead in the establishment of a "big data center" in the medical system of Taiwan, aiming to realize the value of medical big data. Moreover, the Big Data Center is the first research unit with the health care learning and application system as its development core and application demonstration.

 

The primary goal of the Big Data Center is to develop a hospital-wide integrated clinical database. Such a goal can optimize the process of data use and is the first step in building a health care learning and application system. It can effectively integrate the clinical research and knowledge application of different specialties, implement the localization of clinical guidelines and research, and consider individual differences and formulate personalized prevention and treatment, which will make Taiwan's medical care reach the next milestone.

 

The Big Data Center and the information room cooperate closely to carry out the data transfer of the hospital-wide databases. In addition to importing cloud-based data storage management platform, hospital database dimension stratification and architecture star model serial data, it gradually completes the research framework of hospital data, and tests database data and optimizes research processes in a practical way. The Big Data Center also plans to analyze unstructured data (e.g. text and images). Through the integration of structured and unstructured data, it examines the same patient's medical trajectory, which will be able to identify more risk factors or models for quantifiable analysis, provide personalized disease phenotypes, pathogenesis, and disease risk, and carry out personalized precise prevention and treatment.

 

Take kidney disease care, for instance, the Big Data Center has established a kidney database for 13 years. Through analysis, we can find out the markers that can accurately predict the risk of dialysis, cardiovascular disease, and death in chronic kidney disease patients. Such an innovative risk prediction model can be immediately combined with the hospital information system, providing physicians and patients with risk assessments, so that all the people seeking medical attention at CMUH can have intelligent kidney care. The Big Data Center has recently established the first acute renal injury protection network in Taiwan and won a Gold Award for the promotion of innovative application services from the Ministry of Health and Welfare. Through the application of cloud-based health insurance test data, it examines the past changes in the renal function of the outpatients, emergency patients, and inpatients, screening the criteria for the diagnosis of acute renal injury. At present, the hospital management system can not only automatically screen patients for unknown acute renal injury during their visit to the hospital, but also alert the doctor to the preparation of drugs and the imaging examination using the developer, in an attempt to make an early intervention in the treatment of acute and chronic renal disease to improve the patient's kidney safety to the effect of prevention and treatment of kidney disease. These two innovative applications are indeed the best examples of the use of medical big data.The core values of the Big Data Center are to improve big data research power, precision, and competitiveness. The short-term goal is to recruit talents, organize and integrate big data databases, and conduct education training, and through the establishment and integration of an interdisciplinary team build analysis tools and methods. The mid-term goal is to integrate cross-school or cross-college teams and apply big data to business management, services, research and teaching, and set up the Internet of things (IoT) shopping guides and business models. The ultimate long-term goal is to connect various available databases and to realize the commercial value of big data and the value-added industry, academia, and R&D.