Top Applications Of Big Data In Healthcare Industry
The Healthcare industry is one of the few sectors where no mistakes are affordable, even when it comes to modernization. After years of research, we are now seeing what seems like an effortless innovation. The COVID-19 pandemic tested the healthcare sector in many ways; to operate and manage efficiently, many experts relied on technology and data science. Apart from this situational case, healthcare industries use big data to improve diagnostics and ensure minimum human errors that could be fatal. Big data helps in finding patterns in a large population and patients, which in turn gives insights to the institutions. In this article, we will look into the top applications of data science in the healthcare industry.
The Covid-19 pandemic
Healthcare institutions had to quickly adapt to the changes caused by the pandemic. They had to rethink their demand-supply management, relocate and widen their institutions to cope up with the increasing number of patients. Many companies successfully dealt with the situation with the help of big data. Data science and analytics also helped in predicting the possible number of cases and deriving a graph based on the existing data. The incoming data was so overwhelming at one point in the last year that it was very difficult to manage without the help of machines. Data and AI intervention in the scenario helped in determining demographics who have a higher risk from COVID and the effectiveness of vaccines against the virus. At times other than such pandemics/outbreaks, too, hospitals can predict the number of patients to manage the services properly.
Electronic Patient Records
Profiling a customer’s data into an integrated form benefits the healthcare organizations in providing a better opinion to the patient. The profile would include all the medical history of a patient, to avoid misinterpretation of information during diagnosis. Of course, this application can be very risky if the data is not protected by the company to the farthest extent, because there is sensitive information at stake. But again, data science, itself, has the provision of data security, by preventing unauthorized accesses.
Alerting and Patient Engagement
If doctors are able to track the health of patients in real-time, it will be easier to keep the situation under control before a critical stage. Data storage in the cloud enables this application. When the patient is about to enter any critical phase, it pushes a notification to the doctors and healthcare managers. Wearable IoT-enabled devices increase patient engagement, which in turn provides better service. All the technical aspects such as monitoring heart rate, blood pressure, etc become easier.
Strategic Planning and Predictive Analytics
This application is mainly to identify the problems that might not be seen just at a glance. It also analyses the data on a bigger scale and identifies what caused a certain outbreak. The industry calls out to people, in any abnormal situations, to visit a healthcare center and get a check-up done. The automotive tool in this industry has over 30 million electronic records from various sectors and can predict if anyone has any kind of fatal risk in the future.
With the help of AI, ML, and big data, digital platforms available today can provide healthcare without the need for physical presence. Doctors are able to perform operations remotely via real-time data delivery. The process of seeking medical advice is now digitalized with this application. It also saves a lot of time, as the process is quickened and fairly accurate.
The work of doctors and radiologists has become easier as big data analytics introduces itself in medical image evaluation. The machine is trained to detect the flaws by ML. The analysis of specialists is now more efficient, as there is no chance of missing any tiny pieces of information essential for error-free diagnosis. The machine is quite good at using the basics of pathology and anatomy.
Healthcare for Certain Diseases
It used to be quite difficult for people with challenging disabilities and diseases. But after using data for gaining insights, we are able to notice a better quality of life. In a number of cancer cases, doctors could predict the growth and reduce the risk associated with it. It was also detected at earlier stages, and there still is a lot of research going on in the field. Wearable devices for diabetes care has also picked up the pace, which tracks the basic bodily functions and suggests changes in lifestyle if any. Researches are going on to use big data applications to detect HIV in earlier stages as well, and also to provide better care for AIDS patients.