Evaluating a new health care intervention can be a messy and costly process. The gold standard for measuring the effectiveness of a new intervention is a randomized controlled trial, splitting patients into a treated group and an untreated group and comparing the results. But humans are not laboratory animals; they don’t exist in a perfectly isolated environment free from outside influences. Furthermore, because clinical trials are expensive and take years to run, investigators often only get one shot at an evaluation, making it difficult or impossible to learn from the results and continuously adjust the intervention to make it more effective.
Last year, in an ornate downtown Chicago ballroom, the seeds were planted for a new multidisciplinary research network with an ambitious purpose: to understand and improve cities. By mixing together experts in computer science, public health, education, architecture, urban planning, art and social science, the Urban Sciences Research Coordination Network (USRCN) hoped to create versatile and knowledgeable teams that could find new approaches to study cities in a rapidly urbanizing world. Sixteen months later, the early fruits of those new collaborations helped inspire a new wave of discipline-crossing partnerships at the 2nd USRCN meeting, organized by the Urban Center for Computation and Data and held inside the world famous Art Institute of Chicago.