You’ve probably heard or read the phrase, “Big Data” and wondered what that meant. Here’s what it can mean in health care: Collecting millions of bits of information from hundreds of thousands of people and sorting them in a way to help one person at a time.
Today, medicine must take a “one size fits most” approach to treatment. But increasingly, we learn that our individual genetic makeup affects whether a medication works on us, for our particular condition. We’re just beginning to collect data that can make a difference one person at a time, as company GNS Healthcare founder Colin Hill recounts in his father’s battle with cancer.
Big data is “big” mainly because the volume of information compiled is enormous, and comes from many sources. However, the potential impact on individualized medical treatment is just as enormous. Strategically deployed Big Data can not only save lives, it can improve life, and at the same time help bend the cost curve of health care.
Let’s take the 157 million Americans who will be diagnosed with one or more chronic conditions by 2020. Most of these illnesses will be treated with medications. The challenge many physicians report is ensuring these patients actually take their medications.
“Medication non-adherence” has many possible factors: Cost of medication (even for people with insurance), complexity of treatment plan, patient perception of need, and sheer forgetfulness.
Colin Hill’s company, GNS Healthcare (an organization that Cambia has invested in), has partnered with our health insurance subsidiaries to use Big Data to predict who is most at risk for medication non-adherence. We can identify the risks that would keep people from taking medications as prescribed, and tailor a personalized plan that would help them stay on their treatment plan.
What we’ve already learned from this partnership is that there’s a strong relationship between poor medication adherence and increased hospital admissions and emergency room visits. This upholds our premise that not treating chronic disease properly is more costly to the system and more stressful to the individual. Other findings are more surprising: Data analysis leads us to believe that even combinations of medications can lead disproportionally to individuals stopping their treatments.
The goal of personalizing cancer care based on Big Data is compelling, as Colin Hill makes the case for his father. In addition, hundreds of millions of our friends and family struggle with juggling multiple medications for the most common illnesses, such as diabetes, high blood pressure and respiratory conditions.
With health care costs increasing, and the rates of diseases rising fast, Big Data can help us track, study and solve some of the most stubborn health issues that not only drive up costs, but also take a physical toll on our loved ones and our communities.
