A single hospital can store more than 3 petabytes of data at any given time. That’s equal to the contents of the entire Library of Congress. Considering that the United States has 5,546 registered hospitals, you can imagine the massive amounts of data created by our country’s healthcare system. Obviously, the need for data storage and processing is unavoidable, but data is not just a cumbersome side-effect of modern healthcare. It’s a massive opportunity for us to discover, understand and improve, with predictive analytics as the excavator.
Predictive Analytics for Healthcare
Predictive Analytics is the act of forecasting future events, which involves analyzing past and real-time data to identify patterns of behavior that can be transformed into actionable strategies with reduced risk. This risk reduction is made possible by models that allow analysts to test how things like physician behavior, notification systems and other factors influence hospital efficiency, appointment scheduling and cancelations, along with many other outcomes.
The Possibilities are Endless for Medical Applications
For instance, Big Data generated by hospitals can help researchers and analysts determine which diseases are most frequently misdiagnosed, resulting in subsequent hospital visits to properly identify the condition. Understanding which symptoms, ages and weights are most commonly involved in misdiagnosis could lead to the addition of a single test on patient’s initial panel that would eliminate, or starkly reduce, the likelihood of an improper diagnosis. This simple change could greatly reduce the length of hospital visits, increase patients’ chances of survival and free up more room for other hospital visitors.
Cost vs Benefit of Medical Mobile Apps
According to a 2016 survey by Health Catalyst, 8 in 10 hospital executives say predictive analytics will significantly improve the future of healthcare, but only a third of executives are including it in their strategy. In fact, 19% of hospital executives have no plans to use predictive analytics in their practices at all. According to the same study, the number one reason hospitals are falling behind is a lack of tools and infrastructure. A shortage of manpower and restricted budgets are additional factors keeping predictive analytics on the back burner.
A successful first project can open the door to adding predictive analytics to a hospital’s list of priorities and budget. By beginning with a core problem, hospitals can work on building a model that allows them to focus on that factors that contribute to its incidence. Once knowledge is obtained and wisdom is applied back to the problem, the improvement will act as the proof of concept for future predictive analytics projects.
Ready to Make Predictive Analytics Part of Your Practice?
7T has experience working with some of the largest insurance providers in the nation. Call us for advice on applying the power of big data and analytics to your practice for improved operational efficiency and cost savings.