Faced by enormous health care costs and an unsustainable system, more efficient medical practices are needed. Research at the Lucy Family Institute addresses this problem from both ends of the healthcare informatics spectrum. On one end, scholars have focused on the development of analytical models and statistical analysis ranging from lowest levels of personalized care, clinical data, to the highest level of population data to gain additional insights and perspectives into a clinical environment. On the other end of the spectrum work focuses on the development of technologies aimed understanding technology’s role in addressing community based health and wellbeing challenges. Lucy Family Institute researchers are driven by the challenge of bridging the last mile challenge, and making a societal impact through innovations. This research program has formed several partnerships with regional healthcare providers, community organizations, and as well as with international partners.

Combating Child Malnutrition

Lack of sufficient resources, education, and healthcare preempts the ability of children to achieve their personal and collective potential. In addition, the complexity of communities and environment add to the challenges of enabling higher quality of life for children. We posit that addressing the challenges of malnutrition is not just about enabling access to resources and facilities, it is about understanding the true root causes that may stem from the sense of community, family, lifestyle, behavior, and environment. The issues of child health and malnutrition require an understanding and modeling of the early network exposure, and socio-emotional development of the children, including the child’s and mother’s social support network.

Successful Aging

As healthcare becomes increasingly digitalized, we have been working to blend technology with society by developing a healthcare application that can help seniors live better. Our tablet-based application, aimed at enhancing the physical health, vitality, and brain fitness of seniors residing in independent living communities, is a patient-centric framework for medication, nutrition, and pain management designed specifically for senior patients. To help patients manage chronic diseases, the application provides alerts for daily medications and information on medical appointments. The application can also be used as a medium to provide community health workers with discharge summaries. In collaboration with a local Aging in Place program, we have been conducting a study of the application and its effects on senior well-being. Through the study, we investigate conditions indicative of risks or trends in patient health, including questions relating to exercise, diet, mood, and sleep patterns.


MomLink is a research project consisting of a web and mobile application that will help first-time moms access pregnancy-related educational resources and acquire timely and personalized information related to their pregnancy. The application will also allow them to communicate directly with their prenatal care coordination team, receive information, and track their progress.


Through the NetHealth project we are collecting continuous longitudinal data on both people’s social networks and health behaviors in order to (1) test theories about the mechanisms linking social networks and human behavior, and (2) assess the extent to which social influence processes lead to changes in health-related behaviors. Assessing the extent to which social influence operates in social networks is critical for devising future interventions that could harness the power of social networks to reduce incidences of unhealthy behaviors and increase the prevalence of healthier ones. However, empirically determining how important social influence is has turned out to be very difficult. There are other mechanisms besides social contagion through which the observed clustering (i.e., ties among similar people) can occur: self-selection (forming ties with similar others), joint exposure to concurrent exogenous factors, selective avoidance, and high decay rates for ties that do not exhibit trait matching.