Using Big Data to Reduce Costs and Enhance the Value of Healthcare

Big Data is on the tip of everyone’s tongue these days, and it’s no surprise, considering the massive amounts of data we all generate every day. While most industries are already recognizing the value of capturing and analyzing big data, the healthcare industry has just begun to dip its feet in the big data pool.

Over the last few years, research has been conduct to find out how the healthcare sector can leverage big data. In 2012, Ewing Marion Kauffman Foundation released a report stating that providing access to “big data” could be a giant step towards taking control of healthcare costs. The reportdraws attention to areas where the information gleaned from big data could be used to enhance healthcare services. One example states how “combining larger datasets on drug response with genomic data on patients could steer therapies to the people they are most likely to help. This could substantially reduce the need for trial-and-error medicine, with all its discomforts, high costs and sometimes tragically wrong guesses.”

Comparing healthcare today and healthcare two years ago, we already see massive changes, and most of those changes revolve around digital healthcare adoption. The implementation of the Affordable Care Act has further moved the needle toward bringing remote care, telehealth, and other tech-assisted treatments to the forefront in an attempt to lower healthcare costs. These trends have led to a rise in the exchange of electronic health records. That, in turn, has caused clinical data to increase at a more rapid pace. Naturally, the focus has shifted to analyzing these huge data sets in hopes of extracting relevant insights. Healthcare costs aside, if predictive analytics can be properly established, it might help improve both the quality of treatment and the level of care. Here are just some of the key areas where using big data can hope to bring healthcare costs under control.

Re-admissions can be prevented. According to researchers, one-third of re-admissions can be prevented if medical teams have access to the right data sets. This would not only reduce costs but also improve the level of patient care significantly.

More effective triage. Having data-driven insights, such as medical history, immediate symptoms, and other relevant information in one report can help ensure the patient receives the appropriate care and treatment from the get-go. Not only will it allow healthcare professionals to begin treatment faster, but it will also help to prevent complications, that can lead to an escalation in costs.

Adverse events may be controlled. Adverse events, when patients demonstrate negative results during the course of a treatment, are cost-intensive and can lead to high mortality rates. Using big data to monitor these events can help them be avoided. This would not only reduce the costs by shrinking the chances of such events, but it could also save lives in the process.

If we combine all the ways big data can be used in the field, it is easy to see that it has the potential to transform healthcare in amazing ways. Investing in big data analytics will certainly open new revenue streams to the industry and help stakeholders make winning approaches toward offering better patient care outcomes while significantly lowering costs.

Do you agree that big data and its resultant insights could help create a better, more cost efficient healthcare system? Please leave your comments below, we would love to hear what you think.

If you would like to learn more about this and other digital health topics register for MobCon today.

Photo Credit: jamesmaryann29 via Compfight cc