BabyStat - A Simple Tool to Combat the Complicated Issue of Low Birthweight скачать в хорошем качестве

BabyStat - A Simple Tool to Combat the Complicated Issue of Low Birthweight

Team members: Alex Carle, Charlotte Hoo, Ben Robinson, Stephanie Thiede, Mari Tomizawa Low birthweight (LBW) is the leading cause of infant mortality and attributed to debilitating complications in surviving infants that can last into adulthood. For these reasons, there is an associated cost of $20,600 - $52,300 for each LBW newborn in the first year of life alone. Since LBW is primarily caused by non-physiological factors stemming from a mother’s environment or life choices, policy has potential to decrease the prevalence of LBW. Current efforts to reduce LBW are largely aimed at regulating behavioral risk factors; however, little has been done towards regulating pollution levels that contribute to increased LBW prevalence. To make evidenced-based policy addressing issues of LBW, there needs to exist a public health surveillance system that can systematically utilize healthcare and environmental data to efficiently aid policy-makers in recognizing and addressing the issue of environmentally-caused LBW. The design solution is a software tool that allows policy makers to calculate the prevalence and impact of LBW at a county level. Using mathematical modeling, the tool identifies the leading environmental causes and economic impact of local LBW rates. The solution involves a friendly user interface, a back-end database to host data, and models to calculate the impact of environmental factors on LBW and the corresponding economic costs. The solution is the first health surveillance system targeted at policy makers to monitor LBW and provide comprehensive modeling of the condition’s environmental causes and economic burden. Results achieved include the successful completion of a proof-of-concept software prototype that yielded user-satisfaction rates of 90%, modeled environmental correlation to LBW with 70% accuracy, and modeled economic impact with 70% accuracy. With widespread use by policymakers, the solution can bring about policy changes that will significantly reduce LBW and its social and economic burdens.