By Clive Riddle, September 17, 2010
This week, the National Predictive Modeling Summit was held in the Washington DC area. During the Thursday afternoon workshop on International Analytics issues, Rong Yi, PhD, Senior Consultant at Milliman, Inc. gave a presentation on Predictive Analytics and the People's Republic of China.
Here’s some of what Rong had to share on health care and analytics in the People's Republic:
- 22% world’s population, 2% world’s health care resources.
- China’s health care spending is 4.7% of GDP.
- 2/3 of the population are in the rural area, supported by only 20% of health care resources.
- Chronic conditions account for 80% of deaths in China
- Hypertension: 18.1% of population (160 mil), increased by 33% in 10 years.
- Diabetes: 9.7% (92 mil) adult diabetes, 15.5% (148 mil) prediabetes.
- Overweight and Obesity: 8.1% children age 7-17, 22.4% adults
- 14 different ministries and commissions are involved in China’s public health and healthcare policymaking
- Rural Coverage: the New Cooperative Medical System started in 2003, with 100% reach at village level as of 2010
- Urban Coverage: Workers medical insurance started in 1998; Residents medical insurance started in 2007
- Private insurance: Chinese insurers dominant, foreign insurers 5% in market share; Starting in 2011 foreign insurers are allowed to enter the China market for individual and group health insurance
- Reform includes an investment of 2,000 new hospitals in 2009-2012; 3,700 new community health services centers, and 11,000 new community health services stations
- State of Predictive Analytics: (1) No claim-based predictive modeling at the present time; (2) commercial use of scoring methods and HRA tools include- HRA research committee under China’s CDC, Proprietary HRA tools developed on China’s data, and specific scoring tools, e.g., ICU scoring systems, disease-specific scoring; (3) Disease risk prediction models based on health screening data on large population in which long term risks are modified using long-term factors such as lifestyle and behavioral factors (smoking, exercise)