Pools of big data are great places to go fishing for patterns. Scientists and physicians will sometimes engage in long-term studies of specific groups of people to learn if there are any commonalities in how their health progresses. For example, public health workers are currently engaged in a study of 9/11 first responders to learn the long-term effects of their exposure at Ground Zero. Being able to attribute rare cancers and respiratory illnesses they may develop to this exposure arms physicians and the government with more information about how to set up care and support systems.
One of the most impactful cohort studies is the Women's Health Initiative (WHI). Launched in 1993, this long-term clinical trial gathered data on 161,000 post-menopausal women to learn strategies for preventing heart disease, breast and colorectal cancers, and osteoporotic fractures [source: WHI].
The patterns the scientists noted in these women have changed the way health care providers prevent and treat these diseases, bringing a huge return on investment. Researchers employed a disease simulation model over a nine-year range (2003-2012) to compare the differences in women's health based on the findings from the WHI trials.
The model showed that by following the guidelines from the WHI, there were 76,000 fewer instances of cardiovascular disease, 126,000 fewer breast cancer cases and 4.3 million fewer combined hormone therapy users. Further, the disease model simulation showed that by employing the findings from the WHI over that nine-year stretch, Americans saved an estimated $35.2 billion in direct costs for health care [source: National Institutes of Health].