In recognition of the importance of acquiring and rapidly analyzing vast amounts of data, especially in concert with implementation of the Affordable Care Act, the federal government launched a collaborative “Big Data” research initiative. The White House press release of March 29, 2012 stated that six agencies, including the National Institutes of Health, National Science Foundation, Defense Department and Department of Energy, would be involved in developing the technological capacity. Large-scale data accumulation and analysis is essential to accurate economic modeling to assess the effectiveness of new legislation with widespread implications. Meanwhile, advances in health care economics are fundamentally intertwined with advances in data-focused technology.
Just as the government-funded development of “Gopher” in 1991 enabled computer scientists to envision the World Wide Web, the U.S. Office of Science and Technology today aims for a similarly ground-breaking result from its Big Data technology investment. Akin to common perceptions before the World Wide Web, it is beyond our capacity to imagine how Big Data might lead to technological applications in the human sphere. But already technology has enabled medical advances that were once inconceivable. Here’s a look at what might be in store for us with the progress of Big Data:
Smarter Pharmaceutical Testing
A new approach to data is also evolving in research laboratories due to the completion of the human genome project, with pharmaceutical agents being tested against specific biomarkers. Larger data-sets will offer academic medical center researchers the capacity to better share research findings and cutting-edge knowledge.
The ability to better understand the optimal treatment course for a specific patient can also be improved with access to massive data-sets, such as merged patient record, clinical studies, and insurance data, according to Tim O’Reilly et al in an August 20, 2012 blog post in Forbes entitled, “Data Science and the Health Care Revolution.”
Faster Transplant Pairing
Another new approach is the ability to more quickly match organ transplant donors with recipients. The increasing use of Electronic Health Records may be especially beneficial for patients awaiting an organ transplant. Improved analytical capabilities in large-scale data sets could expedite an otherwise lengthy process in which patients can become too sick while waiting to undergo the surgery, particularly in the case of heart and liver transplant candidates.
Better Disease Prevention
Yet another possible approach with the potential to change health care delivery is the merging of public health geographic information systems with other large data sets (e.g., federal prescription database, drug manufacturing data and hospital records). The ability to correlate disease outbreaks to availability of antibiotics or vaccines in a location could greatly reduce transmission rates.
Measuring the effectiveness of preventive health care will also be more accurate with the use of large data sets that can merge hospital records, clinical research results and health insurance databases, and can lead to developing more effective prevention programs in the future. Additionally, preventive measures can be compared for cost-effectiveness.
More Efficient Funding
The Centers for Disease Control has for years maintained databases related to HIV/AIDS cases, and state departments of public health upload data entered from case reports submitted by clinicians. This data is stripped of patient identifying information, but provides a critical understanding of the epidemiologic changes occurring in the HIV+ population. In turn, funding for federal HIV/AIDS services is dependent on this data to assess need and utilization.
The United States government has proven itself capable in the past in protecting patient confidentiality while obtaining data to meet a public health crisis. The government can do likewise with large data-sets of merged medical and insurance data that can enable a better understanding of cost-effectiveness. The ability to contain costs associated with the health care delivery system will be extremely important to reduce federal debt, but not possible without large-scale data-sets and rapid analysis, along with skilled data scientists.
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While budget sequestration now threatens funding for governmental information technology, the need for merging disparate sources of health care data, from medical records to health insurance companies to “clicks” on health information websites, is essential to medical research collaborations to improve health care and provide cost-effective disease treatment. Regardless of how politics play out, Big Data is here to stay, and that looks to be quite beneficial.
