Min Yu and Haibin Wu of the Zhejiang Center for Disease Control and Prevention shared results from their analysis of health data collected from community health centers for diabetes management, diabetes surveillance data, cause of death data and insurance claims data that showed relationships between different patient characteristics and insurance types. The researchers are collaborating with a clinical bioinformatics team at Stanford to use machine learning to expedite the analysis. Katherine Hastings from the Stanford University team, led by principal investigator Latha Palaniappan, presented preliminary ideas about measuring cardiovascular risk with the Atherosclerotic Cardiovascular Disease Risk Score in analyses of Stanford health system diabetic patients. The researchers plan to look into how their overall risk model compares with models for specific subpopulations, such as Chinese, Malay and Indian populations in Singapore. Their work is based on Singapore’s extensive administrative and claims data as well as data provided by the national health surveys conducted every six years by the National Health Service of Singapore. Stefan Ma and Zheng Li Yau of the Ministry of Health of Singapore discussed the 5-year prediction model and statistical methods they used for all-cause mortality of Singaporean individuals with diabetes. He offered to re-estimate the model using the risk factors available on others’ datasets so that the Hong Kong risk model could potentially be used by other teams as well. His next step will be to monetize the value for improved survival in diabetes in Hong Kong. His work primarily looked at how the UKPDS risk engine predicted risk in Hong Kong populations as compared to a local Hong Kong risk engine and how to best calibrate the Hong Kong risk engine. The data sets from those two countries were best estimated by the JJ Risk Engine for the Japan data and the UKPDS model for the Netherlands data.Ĭhao Quan of the University of Hong Kong presented the risk model used for Hong Kong populations. Karen Eggleston, director of the Asia Health Policy Program, delivered introductory remarks and shared current progress by the Japan and Netherlands research teams on calculating value and risk for diabetes with data from the Netherlands and Japan. On the first day, each research team presented its work, describing data sets and explaining the risk models that were used or developed. The goal is to create separate risk models specifically suited for populations from Hong Kong, Singapore, China, Taiwan and South Korea.ĭuring the workshop that spanned two days, the research teams had an opportunity to share updates on their individual projects and to discuss methods and ideas for future collaboration. data and populations, are not very relevant for Asian populations. Previous models used to measure diabetic values and risks, such as the United Kingdom Prospective Diabetes Study (UKPDS) risk engine that was created from U.K. These calculations include monetizing the value of health benefits of new treatments and improvements in health, as well as avoided spending on treatments when prevention was effective, and associated mortality and probability of survival. The research teams from various Asian countries are attempting to calculate the net value of diabetes in those countries by observing the changes in diabetes value and spending. 2009 study with Mayo Clinic Data for Type 2 diabetes. Research teams from Hong Kong, Singapore, China, Taiwan, South Korea and the United States convened at the Stanford Center at Peking University (SCPKU) in Beijing to work on research that compares utilization and spending patterns on diabetes across different countries and to develop a method for measuring the net value of diabetes internationally, based on previous methods discussed in a Eggleston and Newhouse et al. The Asia Health Policy Program at the Shorenstein Asia-Pacific Research Center hosted the Net Value in Diabetes Management Workshop in March to discuss progress on an international research collaboration.
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