The costs of mistakes in the healthcare industry can be devastating. Unfortunately, however, they are not uncommon. The Journal of the American Medical Association found U.S. hospitals waste about $128 billion due to failure to provide care and $192 billion in overtreatment every year, according to FierceHealthcare.
These mistakes are detrimental to financial management and resource conservation, but the impact to patients' health is the most important factor. Unlike other organizations, fixing mistakes after they happen is not an option in many cases. This is one of the primary reasons hospitals turn to predictive analytics to anticipate and avoid problems before they happen.
The future growth of smart systems
Intelligent healthcare solutions, superior data collection and predictive analytics are not only exciting options in today's healthcare management systems, they become downright essential when promising the best care. Many healthcare organization show interest in one or more of these solutions and plan to invest in smarter strategies, according to Health IT Analytics.
With all of these plans for superior intelligence systems, the global healthcare analytics market is expected to see a compound annual growth rate of about 24 percent between 2016 and 2025. Along with intelligent business software solutions, hospitals will look for new ways to collect and input data. Speech recognition, Internet of Things and infection surveillance opportunities should all see substantial growth as well in the next several years.
Managing and collecting data is just the start. To really put resources to best use and ensure patient safety, hospitals will turn to historical information and external details to guide healthcare decisions.
Predicting proper treatment to avoid complications
The predictive analytics market was valued at $760 million in 2014. Thanks to industries like healthcare, it should be worth $2.3 billion by 2022. In a striking example of the practice, The Wall Street Journal detailed how University of Iowa Hospitals and Clinics implemented a predictive modeling software system to reduce the amount of infections in surgery patients.
While a patient's history is a major factor in deciding what post-op treatment to utilize, care plans should also be designed with details of what happened during the surgery itself. The University of Iowa's new practice allows doctors and nurses to input information into intelligent software in the surgery room and in real-time. The system will then deliver insight into the most likely risks and help create a care plan.
In the two-year period the University of Iowa used the information system and predictive analytics tools, infections for colon surgery patients dropped 58 percent. This not only conserves resources and eliminates unnecessary costs, it keeps patients healthy and satisfied with their care.
