Population Sciences

The goal of precision medicine is to broadly improve both individual and population health. To achieve this, we need to fully understand the impact of social, behavioral, environmental and structural factors.

With the help of computational health sciences, and as the knowledge network is developed, patients and providers will be able to see how these factors relate to the individual patient in front of them. This knowledge can improve individuals’ understanding of their health, empower them to make behavioral changes that prevent disease, and improve their compliance with therapies.

Practitioners and patients alike, using digital health tools, will contribute patients’ personal data to the network. Given the size and diversity of the patient population across the UC system, the lessons we learn here will be applicable to people worldwide.

Leading Centers and Initiatives

Driving Projects

Led by the National Institutes of Health (NIH), All of Us is an unprecedented effort to gather genetic, biological, environmental, health and lifestyle data from 1 million or more volunteer participants living in the United States. A major component of the federal Precision Medicine Initiative, the program’s ultimate goal is to accelerate research and improve health.  In California, the program has been implemented by the California Precision Medicine Consortium, which includes  UCSF, UCSD, UCI, UCD, USC, and Cedars-Sinai Medical Center. Dr. Robert Hiatt, MD, PhD, leads the program for UCSF, highlights the importance of having a robustly diverse population in San Francisco and what can be learned by participating.

Led by Alexis Cobbins and Dr. Larry Rand, the Global Preterm Birth Initiative at UCSF Benioff Children’s Hospitals focuses on biological, behavioral, and social factors that drive premature birth, the initiative seeks to define cultural and social barriers to the adoption of healthy practices, and to contribute to the development of new treatments and diagnostic tools. 

The San Francisco Cancer Initiative (SF CAN) is a collaborative effort to reduce cancer in San Francisco by engaging health care systems, government, community leaders, and residents. SF CAN focuses on five (breast, coloreactal, liver, prostate and tobacco related) of the city’s most common cancers likely to be affected by known interventions or better screening. Since many of those cancers affect certain racial and ethnic minorities and the socially disadvantaged more than other groups, a primary focus of SF CAN aim to reduce inequities in prevention, screening rates, access to quality healthcare, and outcomes. 

The UCSF Health Atlas, a new (as of Spring 2020), interactive population health mapping website that curates publicly available data and visualizes it at the census tract level. The UCSF Health Atlas  which will enable researchers to explore neighborhood-level characteristics and see how they relate, also includes regularly updated information on COVID-19 cases and deaths in California. In an effort to encourage UCSF researchers to consider population health principles in their research, education, and clinical care, Health Atlas includes data at the census tract and county level for over 100 contextual characteristics across California. 

Women Informed to Screen Depending on Measures of Risk (WISDOM) is a five-year study that tests two different approaches to breast cancer screening – annual mammography vs. a personalized, risk-based approach. The goal is to determine whether personalized screening is as safe, effective and accepted compared to annual screening. Our personalized screening approach takes multiple risk factors into consideration, including genetic markers, to determine how frequently someone should be screened by mammogram. Over time, we can learn which of these risk factors are most important and continue to adapt our screening recommendations accordingly. This is a UC Health, system-wide study, led by UCSF's Dr. Laura Esserman.