Splash: A platform for analysis and simulation of health

Abstract

As asserted by the Institute of Medicine, sound health policy and investment decisions require use of "what if" simulation models to analyze the potential impacts of alternative decisions on health outcomes. The challenge is that high-level health decisions require understanding complex interactions of diverse systems across many disciplines both inside and outside of healthcare, creating a need for experts across widely different domains to combine their data and models. Splash-the Smarter Planet Platform for Analysis and Simulation of Health-is a novel decision support framework that facilitates combining heterogeneous, pre-existing simulation models and data from different domains and disciplines. Splash leverages and extends data integration, search, and scientific-workflow technologies to permit loose coupling of models via data exchange. This approach avoids the need to enforce universal standards for data and models, thereby facilitating both model interoperability and reuse of models and data that were independently created or curated by different individuals or organizations. In this way Splash can help domain experts from different areas collaborate effectively and efficiently to attack complex health problems. We illustrate Splash's architecture and capabilities using a simple, proof-of-concept model of community obesity. We show how models of transportation, eating habits, food-shopping choices, exercise, and human metabolism can be combined with geographic, store location, and population data to play "what if," asking, for instance, how community obesity measures would change if tax incentives are used to encourage grocery chains selling healthy and inexpensive food to open stores near obesity "hot spots.". Copyright © 2012 ACM.