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Healthcare sector is one of the largest industries in this modern society. The society is always demanding for the better services and treatment for the patient. Providing an effective and efficient service for patients is much more important than in other industries.

The healthcare industry has historically generated large amounts of data, driven by record keeping, patient care, compliance, and regulatory requirements. In traditional days all these data are maintained manually and recorded as hard copies. But this approach fails to provide an extreme service to the patient. Therefore, in the healthcare industry big data analytics offer to provide the best services to the patient through digital handling.

What are Big Data Analytics in Healthcare?

Big data in healthcare is to collect and analyze healthcare data and benefit consumers, patients. The rise of healthcare big data comes in response to the digitization of healthcare information and the rise of value-based care, which has encouraged the industry to use data analytics to make strategic business decisions.

bigdata analytics healthcare

Big data analytics has carved its niche in the healthcare system and has found major improvements such as improved operational efficiency, reduced healthcare costs, improved fraud detection, accurate diagnosis, maintaining patient records and more. The use of big data analytics in healthcare has received positive feedback as well as life-saving results. Big data refers to a large amount of information collected from each department of hospitals and analyzes data by specific technologies.

Why we need Big Data Analytics in Healthcare Industry?

Big data has had a greater impact on various organizations over the years. Healthcare is one of the most prominent areas of optimization of big data analytics. Big data lets users use data and discover new insights to improve or create changes that take action.

bigdata analytics healthcare

The healthcare sector is growing rapidly and it has become necessary to manage patient care and innovative medicines which have grown synonymously. Through big data, health organizations can create patient profiles, detect disease on time, and provide better services.

Big data also helps in managing individuals and population health, predicts health outcomes and designs preventive care accordingly. Healthcare organizations can expect to promote safety, as well, by detecting health care fraud easily and effectively.

Benefits of Big Data in Healthcare

bigdata analytics healthcare

  1. Big data in healthcare helps to personalize care and improve patient efficiency.
  2. It helps in increasing the high geographical potential in the market.
  3. Big data helps promote hospital development by improving care efficiency and patient satisfaction.
  4. It helps to increase marketing activities with information about patients, customers, therapists and preferences.
  5. Inform physician relationship management efforts by tracking physician preferences, referral, and clinical appointment data.

Examples of Big Data Analytics in Healthcare

Predictive Analytics in Healthcare

bigdata analytics healthcare

It is seen that predictive analytics is taking the healthcare sector to a new level. This automotive tool of big data in healthcare helps the doctor prescribe medicines for patients within a second.
Predictive analysis provides patient safety and quality care. It helps keep doctors informed about the patient’s medical history and helps predict future outcomes. For example, some patients suffer from many health ailments and health problems, so this system helps doctors better treat patients using predictive analytics.

Electronic Health Records (EHRs)

bigdata analytics healthcare

Big data has been very useful in healthcare over the last 2 decades. In these 2 years, many hospitals have adopted big data analytics as a primary tool for dependency. This record enables the doctor to conduct in-depth patient care analysis and understand the patient’s illness. This will help improve patient care and improve efficiency.

Real-Time Monitoring

bigdata analytics healthcare

Big data analytics in healthcare helps doctors in real-time monitoring of patient recovery. The main objective of the system is to make patient treatment before they start suffering. Many patients have lost their lives due to delays in treatment and lack of regular monitoring. So, this application helps in real-time monitoring and sharing of data to another doctor so that necessary steps can be taken to treat patients.

Patient Prediction for improved staffing

bigdata analytics healthcare

Staffing is one of the common issues in hospitals. They are facing problems to change a maximum number of people in a given time. If you employ too many workers, you run the risk of adding unnecessary labor costs. Poor customer service results if the hospital caters to some workers.
Big data is helping to solve this problem. Multiple hospitals use data analytics to predict the number of patients in each hospital per hour as well as on a daily basis.

Strong data security

bigdata analytics healthcare

Big data plays an important role in data security, especially in cyber-attacks. Many healthcare organizations started using analytics to help prevent security threats by identifying changes in network traffic.
The biggest benefit is successfully detecting fraudulent claims and enabling health insurance companies to provide better returns on the demands of real victims.

Preventing Human Errors

Many times, it has been observed that professionals prescribe the wrong medicine or mistakenly send a different medicine. This error is common and made by humans. So, Big Data can be leveraged to analyze user data and prescribed medication to prevent this error.

Big data can help cure cancer

Large amounts of data can be used by medical researchers on treatment plans and recovery rates of cancer patients to identify those with the highest success rates worldwide.
For example, the patient’s tumor samples can be examined along with their other treatment records which in turn will help the researchers to perform the treatment accordingly.

Prevention of Unnecessary ER visits

Hospitals want to reduce unnecessary ER visits because they believe that hospitals will fail to provide better results to patients if unnecessary ER visits or emergency visits increase.
For example, a person suffering from acute abdominal pain comes to an emergency room. The doctor will try to find out the cause of the problem such as kidney stones or appendicitis or something else. Using big data analytics, doctors can know the patient’s history and examine patients’ reports. It reduces the time of doctors and gives treatment as soon as possible.

Diabetes Care using Big Data

bigdata analytics healthcare

If we check the history of diabetic patients then it keeps increasing every year. Big data helps to collect behavioral, physiological and contextual data to provide better care for diabetes patients.


Although telemedicine has been around for more than 40 years, it is only today, with the availability of online video conferences, smartphones, and wireless devices that have come into their own.

It is used for primary counseling and early diagnosis, remote patient monitoring and medical education for health professionals.

What is the Future of Big Data in Healthcare?

In the coming future, almost every healthcare organization is going to adopt big data analytics to achieve success. It also helps to make marketing touchpoints smarter and more integrated. With this information, healthcare marketers can integrate large amounts of healthcare insights to find and retain patients with the highest propensity for services.

Abhishek Sharma

Abhishek Sharma

Software Developer

Abhishek is working as a Web Graphics Designer at EzDataMunch. He is involved in Maintaining and enhancing websites by adding and improving the design and interactive features, optimizing the web architectures for navigability & accessibility and ensuring the website and databases are being backed up. Also involved in marketing activities for brand promotion.

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