Transforming Healthcare Through “Big Data”

Oct. 4, 2016
At Independence Blue Cross in Pennsylvania, we are moving forward rapidly to leverage analytics to support the management of care for our members with chronic illnesses

Several years ago, few people would have imagined that their health insurance company could actually prevent them from getting sick, but this seemingly impossible feat is now a reality, with the potential to improve the health of millions of Americans.

By implementing a pioneering new approach to analyzing data, Independence Blue Cross (Independence; we are based in Philadelphia, and serve over two million members in our region, and seven million nationwide) has been able to take advantage of “Big Data” to predict the likelihood of a member being hospitalized within six months and to take action to keep people well. And because keeping people well avoids costly care, this powerful new strategy enables us to deliver better health care at lower costs.

Somesh Nigam

Each time a member fills a prescription, visits a doctor, or undergoes surgery, we collect valuable data on health care usage and outcomes. By drilling down into reams of data and collaborating with patients' doctors and other health care partners, we can now detect patterns and trends early on that can be used to predict and prevent problems down the road.

While this new approach is still relatively young, Independence is already starting to see positive results from implementing Big Data solutions to pressing health care problems. As a national health care organization that serves nearly 10 million people across 24 states and the District of Columbia, we are implementing this strategy in the Philadelphia region. We believe our experience can serve as a model for other health systems and insurers and have found that these approaches lower costs, improve health outcomes, and enhance the patient experience.

One group of people who can most benefit from these new analytic approaches is patients with chronic illnesses. Treating this group of people can be both incredibly costly and also very difficult;  Medicare estimates that it spends $15 billion annually just on preventable  readmissions of these patients.

At Independence, we're helping our members who suffer from chronic illness by using sophisticated algorithms that analyze the equivalent of five Wikipedias worth of information. This data set includes everything from the member’s medical claim and lab results, whether they’ve taken their prescribed medications, hospital admission history to socio-economic conditions. We use this information, for example, to determine how likely these members are to be hospitalized in the next six months.

Then we refer members, such as those with congestive heart failure and COPD [chronic obstructive pulmonary disease], and who are at the highest risk of being hospitalized, to a health coach.  Health coaches coordinate care with members’ doctors and nurses, ensure that the members get proper diagnostic testing and procedures, and even arrange home nursing care and transportation to medical appointments, if necessary.

Though we're only a year into the program, early results show an approximate 40 percent reduction in hospital visits for members with heart disease who participated in this program. This doesn't just translate into health care savings, it means members have more time and energy to do the things they love and to spend time with their families. It also shows that aggressive but tailored solutions to remove obstacles to care and head off problems before they start can make a measurable difference in patient outcomes.

Independence is also partnering with NYU Langone Medical Center to tackle a health care epidemic. Diabetes is one of the fastest-growing chronic diseases in the United States, with more than 25 million people suffering from it today and an additional 80 million in danger of developing the condition. Using claims and lab data, we're identifying patients who may have undiagnosed diabetes so we coordinate treatment. And we're now identifying patients at high risk of developing Type 2 diabetes and working with them to implement targeted lifestyle changes to prevent them from developing the disease in the first place.  We are also working to identify debilitating co-morbidities associated with diabetes, including cardiac, renal, and neuropathy complications.

But improved health care outcomes are only part of the equation. Increasingly, our national health care conversation has focused on what's known as the “Triple Aim” of health care: Reducing costs and improving health care quality while ensuring customer satisfaction. In addition to improving patient health outcomes, Big Data can also help us tackle the final piece of the puzzle.

At Independence, we have begun using new analytical tools to improve customer satisfaction among our Medicare Advantage members. Working with a partner, we analyzed claims and complaint data to identify the patients who are most likely to be unhappy with their customer service experience at Independence. Independence customer service specialists then personally reach out to these members to ensure that their concerns are resolved before they become problems. Within a year of implementing this program, our Medicare members' complaints to federal regulators fell by more than 40 percent.

These early examples are just the tip of the iceberg, but they demonstrate the promise the strategic use of Big Data has to improve our health care system. By identifying trends in health care usage, we can better manage chronic illnesses. This allows us to both keep costs down while improving our members' quality of life and the health of our communities. As an early leader in this field, Independence is committed to continually finding new and innovative ways to benefit our members, and we are excited to see what new innovations other health care providers in markets across the country develop next.

Somesh Nigam is senior vice president and chief informatics officer at Independence Blue Cross (Independence). Nigam leads Independences cutting-edge data initiatives, collaborations, and partnerships to help improve the quality of patient care and lower costs.

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