As the Baby Boomer generation has entered their retirement, pressure on the healthcare system has increased exponentially, and many are at breaking point. Also on the rise is the cost of healthcare. In an April 2016 survey carried out by personal finance site GOBankingRates, 18% cited rising health care costs as their biggest financial burden - above taxes, retirement savings and higher education. There has been a 3600% increase in healthcare spending since 1970, and despite efforts to quell the tide, the rise shows no signs of abating.
While there is a certain degree of profiteering in the healthcare industry, it is still largely the case that the cost of providing treatment is simply too high. Costs must be cut in order to deliver the kind of service needed at a price that can be afforded, while at the same time ensuring that the greater volume of patients coming into hospitals are taken care of. The key to solving these problems is improving the effective capacity of a healthcare system, thereby opening up access, see more patients in a more timely manner, and patients wait less. To do this requires predictive analytics.
Hospitals are now encouraged to gather and use as much data as they possibly can. And it seems many are already appreciating the benefits. An online survey of 136 health professionals conducted in August by Health Catalyst, a data warehouse, analytics and outcomes vendor, found that almost 80% of hospital executives believe healthcare could be improved by using predictive analytics more in their daily operations.
Healthcare provision is slow and waiting lists are long because assets held in the healthcare system - beds, waiting rooms, equipment, surgeons - are so scarce. However, utilization of these assets is shockingly low. Speaking at the recent Big Data & Analytics in Healthcare Summit, Mohan Giridharadas from LeanTaaS, noted that ’utilization of operating rooms is often less than 50%, utilization of infusion chairs is often less than 60%.’ He compared the situation to some queuing in line for a Super Bowl ticket for several hours, only to turn up to the game itself and find the stadium half empty.
The most common solution to increasing capacity is hiring and training new staff. This has the problem of greatly increasing costs.