Healthcare is a primary issue that concerns us all. Unfortunately, the price of quality of healthcare has continued to balloon throughout the years. Modern powers of computing hope to mitigate these costs with data science and data analytics. Through these tools, those in the healthcare industry are exposed to a world of information, which they can utilize for optimization and savings.
Here are the top five benefits of using analytics:
Identify and Reduce Inefficiencies
Using data analytics can help you identify money sucking problems and inefficiencies so they can be addressed. This is why providers use group purchasing organizations to acquire data that help them lower their costs. In a similar vein, Beaufort Memorial Hospital in South Carolina tapped its IT facility to analyze 180 parameters and make reports on key issues. These include follow-up visits, prescription plans, wheelchair transport, and even room cleaning to reduce the lag time in between the issues. They have also identified that by releasing patients who are doing well a half day early, they can save almost half a million dollars each year. Setting small goals has allowed the hospital to reduce the average hospital stay length, which also means they free up more time for patients who are waiting for care.
Reduction of ER Visits
Using analytics to prevent unnecessary emergency room visits has been utilized by healthcare providers for years. As an example, the Bureau of Health in Minnesota discovered that there 1.3 million needless trips were made to hospitals and emergency room in the state every year. These cost medical facilities almost 2 billion dollars annually, with the money going to unnecessary treatments. The group tapped to analyze the root of the problem highlighted that 50,000 residents had made four preventable ER trips due to chronic illnesses. This very same group was given special attention, primary care, and/or community health setting to be more preventive. This cut the health care costs and overall admission since early intervention addressed the problems.
Minimize Unnecessary Testing
In conjunction with the previous category, data analytics can be used to reduce the number of expensive tests being run in a given span of time. As an example, the St. Louis Children’s Hospital was able to minimize the numbers ordered for Dravet Syndrome. Costing $6,000, this rare form of epilepsy leveraged data analysis to discover that tests performed for this syndrome, particularly in infants, is not essential.
Prescriptive Predictive Algorithms
Some institutions developed an algorithm that has the capacity to predict a diabetic patients risk of unplanned medical visits by analyzing body mass index, smoking status, and other health-related diagnoses, which are all highly preventable. Identifying patients who are the most at risk helped health care professionals in managing the disease. The University of North Dakota School of Medicine is the organization responsible for this project with the ultimate goal of providing quality healthcare while minimizing costs.
Augmenting Patient Engagement
A significant factor of healthcare behaviors and outcomes depend on patient engagement as well as their own health and wellbeing. To help with measuring this level of engagement, South Dakota State University developed an algorithm specifically for people with chronic illness. They utilized pre-existing patient data that focuses on behavior to help people become more proactive when it comes to caring for their own self. If you care for yourself properly, you lessen the chances of visiting the hospital, which in turn cuts costs.
Providing the best possible care is paramount for each patient walking through hospital doors, but costs must be kept at a minimum to ensure that those very same doors remain open for years and decade. A tough balancing act this is for any healthcare professional, but one that must be done for the sake of saving patients and securing lives. Using data analytics with predictive capabilities help to reduce costs so that healthcare providers can focus on the more important aspect of patient care.