Rural areas of China have made remarkable progress in reducing adult mortality within the past 15 years yet broadened health insurance was not a casual factor in that decline, according to a new study by an international research team that includes Asia Health Policy Program Director Karen Eggleston.

The New Cooperative Medical Scheme (NCMS), a government-subsidized insurance program that began in 2002-03, expanded to cover all of rural China within a decade. Examining NCMS and cause-specific mortality data for a sample of 72 counties between 2004 and 2012, the researchers found that there were no significant effects of health insurance expansion on increased life expectancy.

The study, published in the September issue of Health Affairs, showed results consistent with previous studies that also did not find a correlation between insurance and survival, although much research confirms NCMS increased access to healthcare, including preventive services, and shielded families from high health expenditures.

Commenting on the study, Eggleston said population health policies remain central to China’s efforts to increase life expectancy and to bridge the gap between rural and urban areas.

Eggleston also noted that multiple factors beyond the availability of health care determine how long people live, and anticipates the research team will continue to explore the impacts of NCMS by extending the study to look at infants and youth.

Read the study (may require subscription) and view a related article on the Stanford Scope blog.

On July 21, SCPKU was the site of a seminar entitled “Medical Big Data Application Assessment and Safeguards.”  Co-sponsored by the Chinese Health Information Association (CHIA) and the China National Health Development Research Center of the People’s Republic of China (NHDRC), this event was the group’s second seminar focused on this topic which gathered over 80 participants including leaders from CHIA, NHDRC, local members of the Health and Family Planning Commission, and academic representatives from universities, medical institutes and pharmaceutical companies. The seminar concentrated on the fusion of medical big data and health care services, decision outcomes, as well as deployment by the State Council and National Health and Family Planning Commission of the People’s Republic of China (NHFPC).

Following NHDRC Director Wei Fu’s opening remarks, Xuefeng Ling, SCPKU Faculty Fellow, Principal Investigator of the Translational Medical Program at Stanford University and co-founder of HBI Solutions, gave a talk on the application of medical big data in decision support. Dr. Ling introduced big data based business intelligent solutions for health management platforms that hold electronic medical records as structured data. Big data based business intelligent solutions have been shown to yield better performance than traditional unstructured solutions in numerous cases including situational awareness, population approach, and risk information.

University of California-Riverside Bioengineering Associate Professor Jiayu Liao followed with a presentation on Chinese medicine and its contribution to medical big data. Dr. Liao cited the latest clinically validated immunosuppressant inspired by Chinese medicine which is cheaper and more effective than its predecessors.  He also highlighted the first reported Non-peptide GLP-1R Agonist with in vivo efficacy and a new fluorescence resonance energy transfer technique, both of which are based on Chinese medicine.

Harvard Professor of Statistics and Director of Graduate Studies Jun Liu, West China Hospital Vice President and Professor Wei Zhang, and Taizhou Pharmaceutical High-Tech District Health Bureau Director Tao Zhang separately presented on medical big data applications in medical management and service, medical service evaluation and applications based on diagnosis related groups, and Taizhou’s demand and practices.  NHFPC Associate Director and CHIA Chairman Xiaotao Jin and Chinese Academy of Chinese Medical Sciences (CACMS) and Academicians of Chinese Academy of Engineering (CAE) Dean Boli Zhang also presented.

Dr. Ling and Health and Development Center Professor Long Cheng closed the seminar with a discussion focused on early investigations into a medical big data application evaluation index system and an international medical big data human resources development cooperation plan. 

On March 30 and 31, 2017, Stanford held two events at SCPKU featuring the latest developments in quantitative finance and financial technology. 

On March 30, the university co-organized with SCPKU, Tsinghua University’s School of Economics and Management and the Department of Mathematics, and Peking University’s  (PKU) Guanghua School of Management and Department of Financial Mathematics, a conference featuring new developments in quantitative finance and risk management with a particular emphasis on trade execution, financial technology, data analysis, and insurance.   This event was the third biennial conference following previous ones at PKU in 2013 and Tsinghua in 2015. Following opening remarks by Stanford Professor of Statistics and Director of Stanford's Financial and Risk Modeling Institute (FARM) Tze Lai, experts from academia and industry including J.P. Morgan, PKU, Tsinghua, Renmin University of China, Daokoudai and the Southwest University of Finance and Economics in Chengdu, shared the latest developments in a wide spectrum of quantitative finance topics ranging from conditional quasi-Monte Carlo methods to China’s peer-to-peer lending market. 

FARM and SCPKU also co-organized a forum on financial technology and portfolio management on March 31.  Due to advances in artificial intelligence and big data technologies, the financial industry is facing tremendous pressure to develop and implement solutions yielding improved operational efficiencies.  This forum convened distinguished academic and industry speakers from quantitative trading, wealth management, asset management, financial consulting, and credit rating firms and agencies to explore the current development and future for financial technology and portfolio management.

Stanford’s Center for Innovative Study Design, with co-sponsors including the Stanford Center at Peking University (SCPKU), the International Society for Biopharmaceutical Statistics and Tsinghua University’s Center for Hospital Management, held a Forum on Regulatory Science and Biomedical Innovations at SCPKU on March 22, 2017. The event gathered more than 60 leaders from the Chinese Food and Drug Administrations (CFDA), Chinese Association of Preventive Medical (CAPM), universities, professional organizations, and R&D experts from domestic and international biopharmaceutical companies.

Over the last decade, significant progress has been made in medical research, disease treatment and general health and well-being.  The Chinese government has called out innovation as a major national strategy to achieve sustainable growth.  At the same time, to address public health and safety, the country’s regulatory agencies are tasked with implementing relevant laws to ensure the safety and efficacy of new products and services before they’re available to the public. The ability of regulatory agencies, laws and regulations to promote innovation while protecting public health is an important research question.  This forum at SCPKU was designed to facilitate a high-level discussion on this topic by scholars from academia from both China and the US, CFDA leaders, and R&D experts from biomedical industries.

The forum was structured with four keynote talks and two panel discussions. Dr. Ruiyi He, the Chief Scientist at the Center for Drug Evaluation of CFDA, delivered a speech on CFDA’s plan to enhance regulations on drug evaluation to promote the development of new drugs. He highlighted some major initiatives to align with ICH (International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use).  In June 2017, China became a member of ICH. Dr. Dechao Yu, founder and CEO of the Innovent Biologics, Inc., gave a talk on opportunities and challenges in innovative biologics in China. He shared his experience in developing Oncorine and Conbercept in China and the needs for regulation reform for innovative new drug applications. Professor Jiqian Fang from Sun Yat-Sen University reviewed the development of the CFDA in the past two decades and called for open, transparent and academic participation in innovative development of drug review and approval regulations. Professor Baoyan Liu, Vice President of the Chinese Academy of Chinese Medicine Sciences, presented innovations in Chinese medicine (CM) using clinical trials and big data, and the regulatory needs tailored for the sciences of CM.

The two panel discussions were focused on the challenges and opportunities in evaluating the safety and efficacy of innovative biomedical products and collaboration in biomedical innovations. Panelists included a CFDA division director, CFDA biostatisticians, several members of the CFDA advisory committee, a vice president of CAPM, and CEOs of several biomedical startups in China.

Attendees were able to exchange ideas in an open and fair environment and many expressed interest in joining future SCPKU-based forums and workshops on this topic.  Forum participants drew the following conclusions:

·   Regulatory science plays an important role in promoting and supporting biomedical innovations.

·   Regulatory reforms should be open, transparent, science-driven, and in alignment with international standards.

·   Low-quality generic drugs should not be supported.

·   Regulatory agencies, academics, and the biopharmaceutical industry should work together on developing science-based policies to make effective, safe and affordable drugs for Chinese patients.

The Center for Innovative Study Design also held a Workshop on Innovative Statistical Methods in Precision Medicine and Big Data at SCPKU on March 23, 2017. Twelve statisticians from the Chinese FDA, Chinese universities and US universities presented their research on advanced clinical trial design, statistical innovations in big data, and applications of machine learning in biomedical data science. More than 60 attendees from local universities (both faculty and graduate students), government, and pharmaceutical companies joined the workshop and had many insightful discussions.