What are the bigdata opportunities in healthcare? Today, BigData techniques are already employed by startups because BigData technology today can be very cost effectively used to perform analytics and gives startups an edge on the cost and capabilities front.
Big what are the opportunities in heatlhcare for established companies? I’ll offer the thought that it can be broken into two main categories. The categories reflect the fact that there are in-place data assets that will be in place for quite awhile. Its very difficult to move an entire infrastructure to a new technology base overnight. It is true that if some semblance of modern architecture (messaging, interfaces for data access) is in place today, the movement can be much faster because the underlying implementation can be changed without changing downstream applications.
The two categories are:
- Move targeted, structured analytical workflows to BigData.
- Enable new analytical capabilities that were previously not viable.
The first category speaks to the area of BigData that can make a substantial ROI appear fairly quickly. There are many well-undestood workflows today inside healthcare Payers, for example, that simply run too slow, are not robust or are unable to handle the volume. Purchasing another large, hardware based appliance is not the answer. But scaling out to cloudscale (yes using a public cloud for a Payer is considered leading edge but easy to do with the proper security in place) allows a Payer to use BigData technology cheaply. Targeted workflows, that are well understood but underperforming can be moved over to BigData technology. The benefits are substantial ROI for infrastructure and cost avoidance for future updates. The positive ROI that comes from these projects indicates that the transition pays for itself. It can actually occur quite quickly.
The second opportunity is around new analytical capabilities. Today, Payers and others cannot simple perform certain types of analytics easily because of limitations in the information management environments. These areas offer, assuming the business issue being addressed suggests it, substantial cost savings opportunities on the care side. New ways of disease management, outcomes research and network performance management can make substantial returns in under 2 years (it takes a year to cycle through provider network contracts and ensure the new analytics has a change to change the business process). Its these new capabilities that are most exciting.
The largest impediment to these areas of opportunity will be change management. Changing the way analytics are performed is difficult. Today, SAS is used more for data management than statistical analysis and is the defacto standard for the analytical environment. SAS offers grid and other types of larger data processing solutions. To use BigData, plans will have to embrace immature technology and the talent that must be hired to deploy it. But the cost curve could be substantially below that of scaling current environments–again paying for itself fairly quickly. Management and groups used to a certain analytical methodology (e.g. cost allocations) will have to become comfortable seeing that methodology implemented differently. Payers may seek to outsource BigData analytics tools and technologies but the real benefit will be obtained by retaining talent in-house over the long run even if some part of the work is outsourced. Because analytics is a core competency and Payers need to, in my opinion, retain some core versus just becoming a virtual shell, BigData needs to be an in-house capability.