Healthcare organizations are increasingly embracing big data to bolster the quality of care while reducing costs, according to a recent survey of senior level executives.
However, 84% note that their organizations face significant challenges to applying big data and analytics technologies. Moreover, only 45% say that their organizations have viable plans in place for making use of the growing amounts of data that are available for them to analyze.
Other notable findings from the survey include:
- Data analytics are being used for revenue cycle management, resource utilization, fraud and abuse prevention, population health management, and quality improvement
- The most common use of analytics – reported by 90% of the respondents – was for quality improvement
- Eighty-two percent of respondents are sharing patient and clinical data with local healthcare organizations
- Two-thirds of the executives note that they’re using analytics to prevent fraud and abuse
While respondents note that administrative and insurance claims data are the most common data sources, unstructured text-based data and device and sensor data are expected to become much more important going forward.
Still, those working to use big data analytics in the healthcare arena are encountering challenges. For example, only 18% of the executives report that their staff members are adequately trained to collect, process and analyze data.
In addition, 16% note they’re addressing this hurdle by hiring third parties such as consultants, while 26% note that they’ve tried to hire more analytics staff, but they haven’t had candidates with sufficient training.
Hiring the leader of an analytics team and associated team members can be challenging for many companies, notes Piyanka Jain a Forbes blog post. That’s because those who have analytical skills also have to align their work with business goals.
Jain notes that the head of analytics, who drives the analytics agenda and leverages the analytics team to execute that agenda, should have three key skills:
- The ability to layout the analytics agenda for the organization to drive growth and revenue using a structured approach
- The ability to build a data-driven culture for training analysts
- The ability to understand what the analysts and the business professionals need to effectively exploit data
“The head of analytics need not be your best analyst or a brilliant data scientist,” Jain adds. “Rather, the role is managerial, part visionary and part evangelist. Yes, the head of analytics should be a competent analyst, but more importantly he or she must be able to communicate the power of analytics, to bolster the KPIs, and demonstrate success in increasing the top line.”