3 Ways Big Data is Making Healthcare Better
Healthcare is in an interesting time in history. Having conquered countless diseases and solved problems that have plagued humanity from its beginning, the industry now faces some of its greatest challenges yet: curing elusive diseases like cancer, AIDS, and Ebola. Then there are the less sensational problems to solve, such as high blood pressure, congestive heart failure, and strokes. Fortunately, there is now a new instrument in the medical bag that is bringing help to the helpers. Big data is delivering insight that can revolutionize the future of healthcare.
1. Big Data is Helping to Improve Patients Outcomes
Which treatments have been most effective for treating this type of patient with this type of disorder?
Big data can be used to analyze the potential treatments for different medical issues and determine through analysis which treatments were most effective, thereby improving the prognosis for future patients. After years and years of treating devastating diseases like cancer, for instance, healthcare researchers have a tremendous amount of data from all over the world regarding different treatments and outcomes on various patients with all kinds of cancer.
Data analytics allows researchers to ask questions of the data, such as, what treatment has been most effective for a 55-year-old African American male presenting with stage II liver cancer? Similarly, doctors can run analytics to determine what produces the best outcome for a 33-year-old Caucasian female with AIDS, or perhaps a 63-year-old Asian male with a specific heart condition. Patients can live longer, healthier lives when data analytics finds the best course of treatment for their condition.
2. Big Data is Helping to Contain Costs
As you can see in the examples above, not having to take a trial-and-error approach to treating diseases saves costs. Instead of having to cycle through various potential treatments to find the one that any given patient responds well to, doctors can drastically reduce or even eliminate much of the trial process and skip right to the treatment with the highest probability of working.
Armed with the data, insurance companies are more likely to pay for a particular treatment, since doctors can prove its potential for being effective. Additionally, insurance companies are more likely to pay for a treatment if they’re relatively certain it’s the right one, and the only one the patient will need to conquer the disease.
But this isn’t the only way big data cuts healthcare costs. Data analytics can help reduce costs for equipment, labor, and medical processes in the same way that it does these things in manufacturing and other industries. Big data can identify inefficiencies, waste, redundancies, etc. so that processes can be streamlined for cost savings and greater efficiencies.
3. Big Data is Helping to Prevent Illnesses Before They Occur
If doctors could identify patients most at risk of developing conditions like obesity or diabetes, they could help the patient avoid it altogether or offer treatments to reduce the severity and effects of the disease.
Which individuals are most likely to develop diseases and disorders like high blood pressure, diabetes, or leukemia? What if healthcare professionals could identify these people years or even decades before they were diagnosed? Preventative treatment is far better than trying to treat a disease in progress, especially when the disease progresses significantly before the patient receives a diagnosis. Big data can help those at risk to eat better, take preventative supplements and medications, and take other steps to avoid developing the disease altogether or to mitigate the seriousness of the disease and its symptoms.
These issues are just part of the first big wave of data analytics possibilities. Can you imagine what the future holds? Visit Syncsort to discuss the ideal big data solutions for your needs today.