Up at 5AM: The 5AM Solutions Blog

5 Ways HHS is Bringing (Big Data) Power to the People

Posted on Tue, Jun 03, 2014 @ 11:44 AM

OpenFDAYesterday, at Health Datapalooza, United States CTO, Todd Park, announced that the U.S. Department of Health and Human Services (HHS) and the Centers for Medicare & Medicaid Services (CMS) had launched initiatives that make tons of much-requested — but hard to get — health data accessible to the public. 

According to HHS Secretary Kathleen Sibelius, the initiatives' purpose is to advance “…transparency and support data-driven decision making which is essential for health care transformation.” 

From untangling Medicare payment data to making more than 3 million adverse drug event reports computer readable, HHS is shedding light on areas that could empower patients to make better health care decisions and help researchers, doctors, and other innovators develop therapies, tools, and processes that lead to better health outcomes. 

The newly liberated data includes:

  1. 2012 In- and Outpatient Hospital Charges is the first annual update to data released by the Centers for Medicare & Medicaid Services (CMS) last spring. The data compares charges to Medicare for the 100 most common services performed at more than 3000 hospitals across the U.S.
  2. The Chronic Conditions Warehouse and Dashboard includes new and updated CMS information on chronic conditions over geographic data; data on disparities within Medicare populations; Medicare prevalence, use, and spending; and customizable population information.
  3. The Geographic Variation Dashboard includes interactive per capita spending data by state and county.
  4. The Research Cohort Estimate Tool allows users to estimate the numbers of Medicare beneficiaries by demographic profiles and/or health conditions.
  5. OpenFDA is the Food and Drug Administration’s effort to provide easier access to “…large, important public health datasets collected by the agency.” OpenFDA is in the public beta stage and it provides searchable, computer-readable data on more than 3.6 million adverse drug event reports. Future releases will include device and food data.

There is no doubt that the vast amounts of data will open opportunities for developers, researchers, and other professional stakeholders. However, it remains to be seen whether non-professionals will take direct advantage of their recently gained access. While the data is more easily accessible, it is far from easy.

More than likely, public health authorities will use the information to understand the particular health care needs of the populations that they serve. We can also envision that organizations would use the data to study diseases in the "real world," apart from clinical trials. This is valuable.

In a video about CancerLinq, the American Society of Clinical Oncologists' (ASCO) developing health IT platform, ASCO president Peter Yu points out that most of what we know about cancer comes from clinical trials; but only 3% of patients are eligible to participate in trials. HSS and CMS data has the potential to advance personalized medicine by presenting clinicians with a broader, more nuanced view of the diseases that they treat.

That doesn't mean that big data hasn't gone mainstream. Non-professionals are clearly interested in data transparency and accessibility.

For example, for the second year in a row, Kojo Nnamdi will present his eponymous, award-winning public radio show from Health Datapalooza today. Nnamdi's Tech Tuesday feature has evolved from bringing in experts to help users navigate the befuddling intricacies of Windows 95 to tackling issues surrounding science and society (incidentally that is the theme of ASCO's 50th Annual Conference) including using data to advance medicine. 

Another nod to individuals' interest in data is Pfizer's Blue Button Plus project. Blue Button Plus literally puts readable clinical trial results in participants' hands which they can then share with their physicians. 

Big Data, you've come a long way.

Tags: health IT, clinical trials, personalized medicine, Big Data, Data Science, FDA


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