Kee Chan, PhD

Kee Chan, PhD is a CHQOER Adjunct Investigator and an Assistant Professor of Health Sciences and Epidemiology at Boston University. Dr. Chan is affiliated with the QUERI HIV/Hepatitis group at CHOQER.  Her research focuses on developing cost-effectiveness analysis for infectious disease management. Current projects include evaluating the implementation of effective HIV testing programs and the introduction of new treatment regimen for patients with Hepatitis C infection. Other research interests relate to dynamic modeling, health policy, and implementation sciences. Dr. Chan received her PhD from Yale University.  

Research Interests:
- Infectious Disease Management (HIV/AIDS and Hepatitis C infections)
- QUERI HIV/HEP C
- Cost-effectiveness Analysis Modeling
- Public Health Genomics (newborn screening and child health)
- Implementation Sciences

Current Research Projects:
HIV/AIDS.  In 2006, the Center of Disease Control and Prevention (CDC) estimated that 25% of the 1.2 million HIV-infected persons in the United States remain undiagnosed.  A variety of approaches to improving the rates of HIV testing has been identified; however, cost-effective strategies in promoting the implementation and sustainability of HIV testing are not well understood.  In collaboration with medical providers and health care managers at the Department of Veterans Affairs Hospital, our IDM group is evaluating the cost impact of implementing novel interventions, such as the clinical reminders, to improve HIV testing rates in the veteran population. We plan to use our models to compare HIV testing and treatment in both VA and non-VA health care settings.  In our IDM group, we develop models to inform policy-makers and health care system managers in their decision-making for effective infectious disease management.     

Hepatitis C infection.   Hepatitis C virus (HCV) infection is a serious problem in the United States, with about 4 million people affected, which includes 1.8% in the US population and 5.4% in the veteran population. Cost evaluations of different drug therapies are needed to evaluate the extent of disease, treatment rates, and treatment efficacy in the Veterans and Non-Veterans population.  With the introduction of new drug in phase III clinical trials, cost-effectiveness studies are required to understand the cost implications for the expensive new therapies in the VA system.  In our IDM group, our study will facilitate the creation of strategies for maximizing the cost-effectiveness of HCV treatment for the VA.

Genetic Screening.  Population-based genetic testing in infants for metabolic disorder and genetic diseases before the manifestation of symptoms can improve survival and save lives. Using mathematical models to evaluate the costs and benefits of implementing a population-based newborn screening program are important to guide policy recommendation and allocation of resources.  Since the publication of the methods (Chan and Puck 2005), in the year 2007, the State of Wisconsin adopted our molecular assay to screen babies for Severe Combined Immunodeficiency Disorder (SCID), and in February 2009, the state of Massachusetts also began a pilot program to screen for SCID in infants.  In 2011, other states are currently consider expanding the number of disorders for screening.  In our IDM group, we plan to develop models to balance the benefits and harms of expanding genetic screening and the impact of new screening recommendations on the delivery of child health services.