With new medical advances every day, it’s no surprise that the healthcare field has a bold new technology that allows doctors and researchers to more easily access and learn about diseases, treatments, and cures.
With new medical advances every day, it’s no surprise that the healthcare field has a bold new technology that allows doctors and researchers to more easily access and learn about diseases, treatments, and cures. This technology, Apache Hadoop, is a big data storage and processing platform that gives healthcare providers the ability to effectively use much more data than has ever been possible.
New uses and applications are being developed and implemented every day to help healthcare providers diagnose and treat diseases, detect and prevent fraud and system errors, collect massive amounts of data for research and prevention, and even help patients personalize their own care options. Several Hadoop use cases in the healthcare and life sciences fields are expanded upon below.
Personalized Treatment Planning
Personalized treatment planning is a way to provide individualized healthcare to patients based on their medical histories, special needs and sensitivities, and personal preferences. Doctors are able to diagnose and treat patients according to their unique personal data by using Hadoop. Applications can update and send analyses in real-time, giving doctors to-the-minute information to help make better medical decisions.
With all the data available on Hadoop, doctors and researchers can more accurately filter in their searches for diagnoses and provide patients with specific care based on the results. Conditions, symptoms, medications, side effects, medical history, and other contributing factors are all correlated together on the platform so that doctors can isolate and study rare variations of diseases and treat patients accordingly. With Hadoop, providers can utilize deduction technology, predictive modeling, and machine learning so that doctors and their patients have all available resources working for them.
Insurance fraud isn’t the only thing healthcare workers have to worry about. If a provider detects anomalies, alerts are sent to the provider immediately, and the organization is able to prevent, investigate, or resolve the issue, saving money and resources in the long-term. For example, providers could be alerted if:
Identical prescriptions for a patient are filled in multiple locations
A hospital overutilizes services in a short period of time
Patients receive healthcare from different locations at the same time
Monitor Patient Vital Signs
In an effort to provide more proactive care to patients, vital signs are monitored constantly, which means that a constant stream of data is being stored. Such a large amount of information needs an able platform, and Hadoop is well suited. Data can be streamed in real-time so doctors are able to make medical decisions based on any changes in the patients’ vital signs. If any changes to the patients’ vital signs are detected on the monitor, an alert can be sent to the doctors, making them more able to solve and prepare for emergencies.
How Will Hadoop Help in the Future?
As applications built on Hadoop continue to expand, more and more patients will have been helped, as doctors will be able to more easily narrow down, identify, treat, and cure diseases and ailments. It is not only a tool for doctors currently — it will help doctors in the future as they research and work toward preventing and curing diseases like cancer, diabetes, and Alzheimer’s. As doctors are able to use data to learn about the strengths and weaknesses of diseases and their treatments, they progress toward cures, side effect-free medications, and better preventative care.
To learn more about Hadoop, read The Executive’s Guide to Big Data and Apache Hadoop.