Big Data – the technology of processing massive dataset is now widely used among healthcare from the past few years. Initially, large organisations were using this technology to analyse their raw data for making accurate business decisions but now, its impact on healthcare is extraordinary.

With this technical advancement, hospitals are using ML and big data like technology to process data and get useful results through pattern recognition, predictive analytics and many other ways. The worldwide market of big data in healthcare is projected to reach $9.5 billion by 2023 at the CAGR of 11.5 percent.

Here are the valuable services big data provides to this sector:

Electronic Data Maintenance:

The biggest advantage of big data analytics can be seen in Electronic Health Reports (EHR) maintenance. EHR contains patient data including check-up reports, historical data, allergic reports, lab tests etc. This information is shared across secure communication channel with the healthcare sectors for providing them useful insights from patient data.

Doctors can make necessary changes to this data according to their research or tests performed on the patient- eliminating extra paperwork. They can also monitor patient activity through EHR to check whether a patient is taking doctors suggested prescriptions.

For a long-term goal, a few organizations are implementing advanced blockchain technology in healthcare to maintain security and log of this data so that it can be used as a valuable input for the future research.

Predictive Analytics:

The role of technologies like IoT, machine learning and big data in healthcare has been increased drastically in the last decade playing an essential role. The billions of sensors used in hospitals throw a significant amount of data every minute. This unstructured data is analysed with big data technology to organise it in an effective way. Further, the machine learning models are trained with this data to get valuable insights such as patient behaviour which is very helpful for doctors’ in decision making.

The machine learning algorithms are very useful in predictive analytics- once the data is organised. Whether it is waste management or the inventory or patient care- this data utilizes well. This technology of designing intelligent models can be easily understood with Machine Learning Course where you can go through the development of various complex models for accomplishing such works. These models are trained with patient data for providing insights for decision making and various other tasks such as drug discovery, pattern recognition etc.

Healthy Lifestyle – Patient Engagement:

Modern healthcare innovations have resulted in the introduction of smart gadgets such as wearables which are very useful for providing health-related data. These smart devices provide information like heart rates which are further used for monitoring disorders in people resulting in the identification of a disease.

One good think about such devices is- a few patient show interest in wearing these gadgets. Thus, they are involved in own health monitoring activity leading towards a healthy lifestyle without making any weekly clinical visits.

Strategic Planning:

The big data technology helps healthcare specialists to make strategic plans on the basis of insights from patient data. Doctors can analyse the report from various locations to identify the obstacles patients face in their health care. Thus, they can deliver a better hospitality to the patients from the various remote locations.

Real-Time Patient Monitoring:

Both public and private hospitals use real-time data analysed data from the various sources to provide useful details of the patient to doctors. The clinical decision support applications organise the data in real-time assist doctors to take prescriptive decisions instantly.

This way, doctors can manage treatment remotely eliminating the costly treatment at home. Since all this information is stored at the cloud, it can be easily accessed from anywhere anytime. Apart from the cloud, a few organisations are using edge and fog computing like technologies at the devices used to collect data. Through it, they can eliminate the unnecessary information at the network node saving the extra cost for storage and effort push by big data for organising this raw or unstructured data.

With the help of historical data, doctors can tell about the delivery and other status of a patient. And, in some cases where instant action is needed such as sudden fluctuation in heart rate of a patient, the administrator is informed quickly take positive steps for controlling this scenario.

Drug Discovery:

Our medical centres are still involved in performing higher and advanced academic research to recognize the cure of various fatal diseases such as cancer. The incredible tools like Watson assist these scientists and researchers in diagnosis, cancer treatment and finding the cure of such diseases. And, the only requirement is the pure data input from historical research, patient treatment etc. On examining this data, researchers can find the cure of such diseases and discover new medicines which provide relief to the patients.

Final Call:

These outstanding works are just not limited to hospitals, even big organisations like Google and IBM are helping this sector to add a new page in human history by providing the solution to this complex problems through automation. Maybe one fine day, they mutually will be able to find the cure of diseases like cancer which has taken lives from the human heart.