New faculty member Prof. Zhang starts $400k grant

Prof. Jingwen Zhang just joined the Department this fall, and has already received a grant for a collaborative project with the project's PI Dr. Damon Centola, from the Annenberg School for Communication at the University of Pennsylvania. The Robert Wood Johnson Foundation Pioneer Portfolio funds for projects that pursue innovative approaches to solving problems in health and healthcare.

The grant-winning project title is:

Using network science to reduce variance in and increase accuracy of physicians' decisions that impact treatment assessments and medical costs

Amount: $390,041

Grant period: September 1 2016 to August 31 2018

Abstract:

The Affordable Care Act contains broad provisions for targeting high healthcare costs, intended to reduce regional variation in quality and cost of healthcare. However, the ACA addresses financial incentives while overlooking the fundamental problem of how social influences cause variance in quality of care and medical spending. Our proposal is to adopt an innovative approach to this problem that uses network science to reduce the variance and increase the accuracy of physicians’ decisions. Our approach is based on the idea that there is an untapped pool of collective wisdom in physician networks. A particularly promising finding known as the “wisdom of the crowd,” suggests that a group’s collective judgement can be more accurate than the average judgements of its members. This phenomenon holds great promise for medical organizations and health systems to form accurate evaluations of treatment assessments and medical costs despite errors in individual judgement. However, several decades of research has found that the wisdom of the crowd effect can be easily undermined by social influence. Social influence can create herding effects that increase variance across regions and undermine available expertise by creating norms of practice that may mitigate efforts to improve medical practices. Our solution to this problem uses recent advances in network science that suggest ways in which network structure can mediate the effects of social influence.