5 Big Data Trends in Healthcare for 2017
The healthcare industry, perhaps more than any other, is on the brink of a major transformation through the use of advanced analytics and big data technologies.
In this post, we’re going to talk about 5 big data trends in healthcare for 2017.
A goal of modern healthcare systems is to provide optimal health care through the meaningful use of health information technology in order to:
Health payors such as insurers and public health systems (e.g., Medicare and Medicaid) are in the early stages of shifting from fee-for-service compensation to value-based data-driven incentives that reward high quality, cost-effective patient care and demonstrate meaningful use of electronic health records. This approach requires significant improvements in reporting, claims processing, data management, and process automation.
The focus on value-based care corresponds with an increased focus on patient-centric care. By leveraging technology and focusing healthcare processes on patient outcomes, a continuum of care, doctors, hospitals, and health insurance need to work with each other to personalize care that is efficient and price conscious, transparent in its delivery and billing, and measured based on patient satisfaction.
Thus, the goal now is to begin to move more decisively away from the long-standing fee-for-service practice by which payments are made to providers. In essence, providers get paid for seeing and treating patients. Currently, there is little or no reward when and if providers improve quality of services, boost patient outcomes, or reduce costs. Fee-for-service has been a major roadblock in plans or desires to invest in digital solutions to, say, improve patient outcomes if the providers cannot recoup their investments. As one senior executive at KPMG put it, “Instead of rewarding leaders for transforming healthcare, our systems reward leaders for making narrow improvements within them.”
Current thinking around long-standing, crucial payment practices is beginning to change, paving the way for a robust digital transformation of healthcare.
Also called the Industrial Internet, these terms refer to the rapidly increasing number of smart, interconnected devices and sensors and the tidal volumes of data they will generate and move between devices, and ultimately to people. Spending on healthcare IoT could top $120 billion in just four years, by some estimates. And most of the data created by the healthcare IoT is of the unstructured variety, creating a major role for Hadoop and advanced big data analytics working within the Hadoop framework.
Today, a variety of devices monitor every sort of patient behavior – from glucose monitors to fetal monitors to electrocardiograms to blood pressure. Many of these measurements require a follow-up visit with a physician. But smarter monitoring devices communicating with other patient devices could greatly refine this process, possibly lessening the needs for direct physician intervention and maybe replacing it with a phone call from a nurse. Other smart devices already in place can detect if medicines are being taken regularly at home from smart dispensers. If not, they can initiate a call or other contact from providers to get patients properly medicated. The possibilities offered by the healthcare IoT to lower costs and improve patient care are almost limitless.
The cost of fraud, waste, and abuse in the healthcare industry is a key contributor to spiraling healthcare costs in the United States, but big data analytics can be a game changer for healthcare fraud. The Centers for Medicare and Medicaid Services prevented more than $210.7 million in healthcare fraud in one year using predictive analytics.
