Big data could help US citizens save up to $450 billion in healthcare
Big Data is making its way into the healthcare sector as well with more pharmaceutical companies recording years of research and development data into medical databases, while payors and providers have digitized their patient records.
According to a McKinsey report, the US government and other public stakeholders have been opening their vast stores of healthcare knowledge, including data from clinical trials and information on patients covered under public insurance programs. Recent technical advances have made it easier to collect and analyse information from multiple sources—a major benefit in healthcare, since data for a single patient may come from various payors, hospitals, laboratories, and physician offices.
Fiscal concerns are driving the demand for big-data applications. Healthcare expenses in the United States now represent 17.6 percent of GDP—nearly $600 billion more than the expected benchmark for a nation it’s size and wealth. To discourage overutilization, many payors have shifted from fee-for-service compensation, which rewards physicians for treatment volume, to risk-sharing arrangements that prioritize outcomes. Under the new schemes, when treatments deliver the desired results, provider compensation may be less than before. Payors are also entering similar agreements with pharmaceutical companies and basing reimbursement on a drug’s ability to improve patient health. In this new environment, health-care stakeholders have greater incentives to compile and exchange information, it reported.
Although the health-care industry has lagged behind sectors like retail and banking in the use of big data—partly because of concerns about patient confidentiality—it could soon catch up. First movers in the data sphere are already achieving positive results, which is prompting other stakeholders to take action, lest they be left behind.
Healthcare stakeholders are well versed in capturing value and have developed many levers to assist with this goal. But traditional tools do not always take complete advantage of the insights that big data can provide. Unit-price discounts, for instance, are based primarily on contracting and negotiating leverage. And like most other well-established healthcare value levers, they focus solely on reducing costs rather than improving patient outcomes. Although these tools will continue to play an important role, stakeholders will only benefit from big data if they take a more holistic, patient-centred approach to value, one that focuses equally on healthcare spending and treatment outcomes
During a recent scan of the industry, McKinsey found that interest in big data is not confined to traditional players. Since 2010, more than 200 new businesses have developed innovative healthcare applications. About 40 percent of these were aimed at direct health interventions or predictive capabilities. That’s a powerful new frontier for health data applications, which historically focused more on data management and retrospective data analysis.
McKinsey evaluated a range of healthcare initiatives and assessed their potential impact as total annual cost savings, holding outcomes constant, using a 2011 baseline. If these early successes were scaled up to create system-wide impact, it estimated that the pathways could account for $300 billion to $450 billion in reduced health-care spending, or 12 to 17 percent of the $2.6 trillion baseline in US health-care costs. The estimate of $300 billion to $450 billion in reduced health-care spending could be conservative, as many insights and innovations are still ahead.
- Advanced Analytics: A Top Business Priority
- Ways To Bridge The IT Skills Gap
- Big Data Still In Its Infancy, Say Researchers
- Red Hat Signs Big Data Deal With Cloudera
- Ways To Secure Your Enterprise Cloud
- Open Source To Dominate eCommerce Market In India
- Automation, Simplicity To Drive Data Center Mgmt
- Can SAP-IBM Deal Keep Oracle, Amazon At Bay?
- What Is A Successful Big Data Strategy
- Using Analytics To Prevent Banking Fraud