Kauffman: Leverage big data to control healthcare costs
Providing access to “big data” is a giant step to curing many healthcare ills and taking control of the healthcare costs, according to a new report released today by the Ewing Marion Kauffman Foundation, a private non-partisan organization.
The Kauffman Foundation Task Force put forth incremental approaches to achieving efficient healthcare reform – to address what it called "America's most urgent public policy problem.”
[See also: How to harness Big Data for improving public health.]
The foundation released its report April 19 at the The Atlantic's fourth annual Health Care Forum in Washington, D.C. The event focuses on improving the cost-benefit balance in American healthcare through open access to medical data.
The report, "Valuing Health Care: Improving Productivity and Quality," is based on the recommendations of 31 experts from related fields convened by the Kauffman Foundation to reframe thinking around the question, "How can the productivity and value of American health care be increased, in both the short-term and long-term?"
While acknowledging that there's no shortage of reports and recommendations for healthcare reform, the task force members say they took a unique approach to tackling health care value and productivity challenges.
"Rather than look for a 'one-shot-fix' solution, the task force focused on incremental reforms that cumulatively can both reduce costs and enhance the value of healthcare delivered to Americans, regardless of whether and how the Affordable Care Act is implemented," said Robert Litan, vice president of research and policy at the Kauffman Foundation and a task force co-organizer. "The underlying thread to the recommendations is leveraging big medical data."
[See also: 4 tips for leveraging big data.]
"Using proper safeguards, we need to open the information that is locked in medical offices, hospitals and the files of pharmaceutical and insurance companies," said John Wilbanks, Kauffman senior fellow and an author of the report. "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."
Specifically, the report recommends:
- Unleashing the power of information by breaking down silos and encouraging data sharing among research centers, medical offices, pharmaceutical companies, insurance firms and others; and that a new corps of data entrepreneurs be incentivized to collect and analyze existing medical data to discover and then disseminate new therapies.
- Funding more translational, cross-cutting research, with larger average grants made available to larger teams, many of them with participants from multiple institutions; and requiring collaboration across research institutions.
- Reforming medical malpractice systems to streamline new drug approvals and remove counter-productive restrictions on health insurance premiums.
- Empowering patients by, among other means, providing unbiased information on treatment options' benefits and drawbacks, and helping them make choices about the relevant lifestyle implications and risk-reward tradeoffs.
Further, the task force contends, healthcare delivery deserves its own national research program, one focused on comparative efficiency research. As the task force puts it, more efficiency (with acceptable quality guidelines) leads to profitability, and corrects the easy practice of simply passing costs down the health care stream.