If you watched the Sochi Winter Olympics you know that Bob Costas, NBC’s favored face and voice of nine Olympic games, was sidelined for several days by a raging eye infection. Had Costas somehow seen it coming, perhaps he could have taken measures to prevent the disease entirely, or at least keep it from worsening. After all, that is the direction that healthcare is headed. All thanks to Big Data analytics.
Today’s healthcare industry is bursting with all kinds of data about patients, conditions, treatments, drug protocols, outcomes, etc. The problem is that this type of data is unstructured, making it difficult to capture and analyze by traditional means. However, through the use of cloud and warehouse-based big data analytics platforms, it’s now possible to access and analyze disparate healthcare data to gain actionable insights—insights that can lead to improved patient care and better outcomes.
One area of healthcare that big data is making a major impact on is preventive care, helping doctors ward off diseases before they have a chance to take hold. Here’s a look at big data’s rising role in preventive healthcare.
Health monitors and alerts - Health monitors provide a constant stream of physiological data, such as a patient’s vital signs, that healthcare providers can use to assess the patient’s condition. However, subtle changes in heart rate, or respiration that could indicate a worsening of the patient’s condition can be too subtle to trigger an alert. In addition, this rapid and prolific flow of data is too much for the mind to process in real time. Consequently, these early warning signs can go unnoticed. However, thanks to big data platforms that can analyze health monitor data in real time, these subtle early warning signs can be detected as soon as they appear. When doctors are alerted to these anomalies, they can respond quickly with measures to prevent the patient’s condition from worsening. The ability to detect impending problems, such as infections, heart attacks or strokes, and intervene with treatment early on can be life saving.
Predictive diagnostics – At the University of Notre Dame, Nitesh V. Chawla, an associate professor of computer science, and his doctoral student Darcy A. Davis, recently developed the Collaborative Assessment and Recommendation Engine (CARE). The primary purpose of the system is to sift through mountains of health population data and capture patient similarities to generate a personalized disease risk profile for individual patients. As far as the practical application of CARE in the real world, Dr. Chawla recently told the Notre Dame News that, “In its most conservative use, the CARE rankings can provide reminders for conditions that busy doctors may have overlooked.” Chawla went on to say that, “Utilized to its full potential, CARE can be used to explore broader disease histories, suggest previously unconsidered concerns and facilitate discussion about early testing and prevention, as well as wellness strategies that may ring a more familiar bell with an individual and are essentially doable.” With these types of benefits there is no question that analytics systems such as CARE will become an invaluable tool for doctors and their patients.
Proactive patient care – Through big data analytics, predictive care is giving rise to proactive care. Paraphrasing Dr. Chawla, the Notre Dame News article pointed out that, “the core premise of CARE is centered on patient empowerment and patient engagement.” Chawla proposes a scenario wherein patients walk into their doctor’s offices with health related questions and concerns, only to walk out with a personalized list of lifestyle change recommendations that are based on their own big data predicted health risks. Knowing that implementing the suggested lifestyle changes could help ward of debilitating and life threatening diseases, patients should become more proactive with regard to their own health and well being.
Reduced readmission rates – A natural result of big data’s role in predictive and proactive patient care is reduced readmission rates. And another way that big data can lead to fewer readmissions and hospitalizations is through big data analytics behind the pharmacy counter. Using sophisticated software programs that can detect harmful side effects and drug-drug interactions, pharmacists can help doctors tailor their patient’s drug regimens to optimize therapeutic outcomes while mitigating risks.
Reducing costs – As healthcare costs continue to soar, the cost saving benefits of big data will become more apparent. According to Chawla, “There is an increased focus on preventive care, well-being and reducing re-admission rates in the hospital. This system can help bend the cost curve.” With so many benefits, it’s easy to understand why the healthcare industry has been such an early adopter of big data technology. It will be interesting to see the impact big data has on the health industry moving forward.
Author Bio: Gil Allouche is the Vice President of Marketing at Qubole. Gil began his marketing career as a product strategist at SAP while earning his MBA at Babson College and is a former software engineer.
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