To See Is to Believe-Visualization of the Spectrum on Chronic Kidney Disease

Disease is a collection of many sub-diseases with multi-dimensions, multi-variations and time oriented, which becomes very complex and difficult to define. Usually the pathogens affects by interacting micro and macro environments among patients and enhance the progression and development of chronic diseases with a variety of comorbidities. Therefore, the health care professionals and patients should think in multi-dimensional directions to understand the disease progressions. “A picture is worth a thousand words“ is the biggest advantage of visualization. In this study, a huge amount of data and innovative multi-dimensional visualization method will be used to render the state of the disease. Data visualization process will includes data generation, data conversion and visual presentation. Chronic kidney disease (CKD) will used first as an example in this study as 2 million patients only with CKD disease burden in Taiwan from 23 million whole population. Out of that 2 million CKD, 60,000 patient undergoes Hemodialysis (HD) which cost 30 billion NTD per year which is increasing day by day. It will have high risk factor for hypertension, DM, smoking, Obesity especially on low social society level. We will use National Health Insurance Database which covers whole population of Taiwan to extract these patients records and the build a database through the clinical specialties physician‘s advice, to understand the progression of chronic kidney disease with data processing to find the targets, and then use algorithms to turn data into visual charts and identify different types of users among all users to apply visual analysis and graphics. These results will help clinicians to diagnose the disease along with interactive visualization system together with the patient treatment decisions that would improve health care quality, reach the patient in terms of prediction and prevention of disease, and reduce induced disease probability. In terms of medical education, it will be helpful to take advantage for multi-dimensional perspective of the disease diversification, three-dimensional, and presents the evolution of the disease through visualization. Based on these big data visualization results with disease patterns for CKD, the policy makers can get the real benefits to know clearly with evidence and then it will help them for policy implications and regulations in health care sector and to monitor and control chronic disease burdens.