A Prediction of Number of Patients and Risk of Disease in Each Region Based on Pharmaceutical Prescription Data

의약품 처방 데이터 기반의 지역별 예상 환자수 및 위험도 예측

  • Accepted : 2018.01.24
  • Published : 2018.02.28


Recently, big data has been growing rapidly due to the development of IT technology. Especially in the medical field, big data is utilized to provide services such as patient-customized medical care, disease management and disease prediction. In Korea, 'National Health Alarm Service' is provided by National Health Insurance Corporation. However, the prediction model has a problem of short-term prediction within 3 days and unreliability of social data used in prediction model. In order to solve these problems, this paper proposes a disease prediction model using medicine prescription data generated from actual patients. This model predicts the total number of patients and the risk of disease in each region and uses the ARIMA model for long-term predictions.


Supported by : Ministry of Education in Korea


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