News for Predictive Analytics Continues to Flow
A recent article in the WSJ once again highlights the steadily growing list of applications for predictive analytics in health/life science. This time the goal is identifying patients likely to stop their medication regimen before they do so.
According to a report from the nonprofit New England Healthcare Institute, an estimated one half to one-third of Americans don’t take their medications as prescribed by their doctors…contributing to about $290 billion a year in avoidable medical spending including excess hospitalization.
Is it any wonder with that level of cost at stake along just one vector in health care science that the demand for the best in predictive analytics is becoming more and more critical?
Significant cost savings across the entire spectrum of health care science, as well as more individualized service options for patients, are expected as inevitable results of the steady powering-up now seen in predictive analytics. There are many opportunities to review the positive results in applied case studies. These provide just a glimpse at the successes ahead.
Take for instance the results of SSPS technology and software at Texas Health Services, where the challenge was to limit health care costs without reducing the quality of service provided to patients. As Texas Health Services relates:
“With IBM SPSS Statistics Base, Texas Health Resources has greatly enhanced its ability to support its process-improvement initiative. Today, it not only detects process variations, but can determine the underlying causes such as a sicker-than-normal patient population.”
Data quality was improved while data mining costs were reduced by 50 percent.
These high yield results make it clear why developments in predictive analytics have become so worthy of front and center news for so many segments of the health care industry. Other endeavors are focused on identifying those individuals most likely to develop specific illnesses such as develop diabetes or cancer. Ingenix, a unit of United Health Group, and a customer of Netezza, has already successfully launched an effort to mine and analyze the underlying risk factors in patient data before an illness develops or advances.
As health care science, quality patient care and advancing medical technology struggle with cost factors, the value of predictive analytics in lowering costs increases exponentially.