Solving America's Big Health Care Challenges With Big Data

Living with diabetes and working with big data, I see a revolution in how we can treat diseases using tiny health measurements at a global scale.
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I have type-1 diabetes. Along with almost 30 million other Americans, I manage my symptoms and wait for the next technological innovation that will help me live better.

However, unlike most of my fellow patients, I work in the technology sector, so I have the privilege of watching tech geniuses tackle these innovations right before my eyes.

Every day, my colleagues work tirelessly to create better tools for our customers and partners, collecting massive amounts of our planet's data and analyzing it to derive life-changing insights. The application of these insights can save lives, whether by speeding up cancer research, providing more reliable research data, or getting supplies out faster to victims of natural disasters. It's a huge responsibility I can't take lightly, and I live with a daily reminder of what's at stake.

For the uninitiated, everyday information accumulates into what we call "big data" once the sheer volume of it can no longer be stored on traditional hardware or managed using traditional databases. Make no mistake -- our civilization has moved beyond the Information Age to the Age of Big Data. Ninety percent of the world's digital data was created over just the past two years. What's more, the amount of new data is doubling every 18 months.

Consider the following: Every day, I constantly monitor my blood sugar level -- this information is crucial for me to manage my symptoms in the short term. In the past year alone, I've received more than 5,000 alerts warning me that my levels are too high or too low. I've collected more than 565,000 rows of data about my blood sugar -- I am big data, and you are too.

Living with diabetes and working with big data, I see a revolution in how we can treat diseases using tiny health measurements at a global scale. I want the blood sugar data I record to get sent automatically to my physician, who could get alerted of any disturbances in my blood sugar that would change my treatment plan. I want that data to go to a government health agency and health care organization to contribute to researching this national health care challenge. Imagine the incredible impact my readings, anonymously collected and added to the 30 million other readings out there, could have on health care professionals to identify trends, analyze effective treatments, predict outcomes and improve long-term patient care.

Already, big data abounds in the health care industry. In its 2011 report titled "Big Data: The next frontier for innovation, competition, and productivity," the McKinsey Global Institute estimated that more than $300 billion a year in new value can be created in health care by 2021, with two-thirds of that coming from reductions to national health care expenses.

The scenario from my personal life is just one example of how clinical data can be leveraged. In payment and pricing, we'll see dramatic improvement in fraud detection as well as the application of adaptive pharmaceutical pricing and reimbursement. In clinical operations, we will conduct comparative research more productively, while achieving more accurate clinical decisions and advanced patient profiles. In medical research and development, we can use predictive modeling to better design clinical trials and offer personalized medicine.

Making this a reality will require the public sector to embrace technology at a level equal to the private sector. Already, federal and state IT officials recognize the benefit of big data technology. According to a study released this year by TechAmerica, 87 percent of federal IT officials and 75 percent of state IT officials believe a nationwide use of real-time big data has the potential to save a significant number of lives each year.

The reality is that the United States spends about 30 percent more on health care than the average Organization for Economic Co-Operation and Development (OECD) country while falling below average in life expectancy and infant mortality. This isn't a sustainable trend.

We're spending too much money and not seeing a return on that investment in terms of healthy, happy people. According to one recent estimate, big data could result in annual savings of up to $450 billion in health care spending. As a nation, we need to reprioritize our health care spending and put the massive amount of medical data that's already out there to intelligent use.

We have many hills to climb in health care, including skyrocketing costs, a rise in insurance fraud, and protecting patient privacy. By removing the technology barriers that prevent us from moving forward, I see a future in which the United States dramatically lowers costs, radically improves treatment accuracy, and facilitates access to life-saving drugs.

From the cradle to the grave, we never stop generating data. Every heartbeat, every commute, every purchase, and every interaction adds to the growing cacophony of information. As a diabetic, I'm encouraged that we have powerful enough tools in my lifetime to reach into that noise, isolate the notes that ring true, and share the resulting symphony with the whole world.

Steve Lucas is Executive Vice-President of Business Analytics, Database and Technology at SAP. SAP is the world leader in enterprise software and software-related services.

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