Continued efforts to use big data in healthcare and make it more widely accessible could play a significant role in lowering overall costs, the authors of a new report published this week argue.
The report--rolled out by the Kansas City, Mo.-based Ewing Marion Kauffman Foundation, which promotes entrepreneurship--makes a number of specific recommendations, including points regarding data use in both patient care and medical research.
For instance, the authors say that all of the nonprofit organizations that study disease should collaborate to build a national health database. They add that future job-related health benefits packages could provide direction on how employees could contribute their own health information to such a database.
Additionally, the authors call for increased public and private comparative effectiveness research efforts, pointing out that the 2009 stimulus bill and the 2010 Affordable Care Act call on the federal government to fund and conduct more comparative effectiveness studies.
"Efficiency research on the delivery system deserves the same level of attention from federal funding as research on new treatments," the authors say. "Employers can and should demand that providers do a better job of tracking efficiency and subject healthcare costs to the same kinds of negotiations with vendors as are other expenses and inputs. The government should report Medicare data with a lag of weeks or months, and the cost to receive it should be reduced."
The report comes at a time when the healthcare industry is abuzz about big data initiatives. For instance, late last month, the Obama administration announced it was putting $200 million behind a big data effort that will benefit several industries, including healthcare and health IT.
Additionally, Amazon and the National Institutes of Health also announced in March that, through completion of the 1000 Genomes Project, 200 terabytes of genomic data now are publicly available free of charge.
Using proper safeguards, we need to open the information that is locked in medical offices, hospitals and the files of pharmaceutical and insurance companies," Kauffman senior fellow John Wilbanks, one of the report's authors, says in an announcement. "For example, combining larger datasets on drug response with genomic data on patients could steer therapies to the people they are most likely to help. This could substantially reduce the need for trial-and-error medicine, with all its discomforts, high costs and sometimes tragically wrong guesses."
Experts providing insight for the report include individuals from Duke Medical Center, the Mayo Clinic, the West Wireless Health Institute, Stanford University and Yale Law School, as well as several other institutions and organizations.
To learn more:
- here's the report (.pdf)
- check out the accompanying announcement