Data pools, information overloads, figure collection – whatever you wish to call them – these conglomerations of information hold a great deal of potential in the healthcare field. From predictive diagnoses to determining which treatment options provide better results, big data is working to overhaul the way healthcare is performed.
As for the figures themselves, these growing data pools are located virtually everywhere. By collecting patient information every time a person arrives for treatment (or a prescription, or enters their info online), companies can keep track of demographics and their respective ailments. Over time, patterns begin to emerge as to what ages are more likely to develop which sickness, and so on.
By crunching and analyzing it to find repetitions and similar situation outcomes.
For instance, in 2008, the California Public Employees’ Retirement System (CalPERS), the second-largest healthcare purchaser in the nation, set out a plan to reduce their costs. Within its first year, the plan did not increase patient fees (previously costs increased 8-12 percent per year), while saving more than $15.5 million.
Through the help of analytics, CalPERS was able to lower expenses just by predicting subsequent patient care. This study included 41,000 of CalPERS’ 1.3 million employees, and reduced fees through:
- 15 percent reduction in inpatient readmissions – within 30 days of plan enactment
- 15 percent reduction in inpatient days per 1,000 hospitalized study participants
- 50 percent reduction in inpatient stays of 20 or more days
- A half-day reduction in average patient length of stay
The study looked to monitor:
- Population-specific utilization management – through a coordinated operational infrastructure (such as big data analytics)
- The elimination of unnecessary utilization and non-compliance
- Improved clinical and resource variation among physicians
- Reduced pharmacy and utilization costs, among other areas of data
By combining efforts and recreating CalPERS study on a wide-scale scheme, their success rates can grow only respectively.
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