Examples of Big Data in Healthcare

Healthcare may be the field where big data has the most significant potential to improve people’s lives. For example, big data is predicted to permeate the healthcare industry faster and more profoundly than other sectors. According to a recent report, the worldwide healthcare big data industry is expected to increase at a CAGR of 22.07 percent to reach $34 billion by 2022. According to a new comprehensive analysis, big data in healthcare is expected to grow at a CAGR of 36% by 2025.

Many healthcare companies lack the necessary systems and databases and the staff required to manage them effectively. Consequently, there is a massive demand in the United States for healthcare analysts with extensive education and training. The easiest way to start dealing with big data in healthcare is to take the best big data course available.

What do you know about big data?

Big data is often characterized as a vast quantity of complex data, either unstructured or structured. It can efficiently leverage that to find deep insights and solve business challenges that it couldn’t solve before using conventional analytics or software. Data scientists commonly use artificial intelligence-powered analytics to analyze these massive datasets to identify essential business patterns and trends.

What is Big Data in healthcare?

“Big data” in health care refers to significant amounts of information generated by the use of digital technology that collects patients’ records and assists in the management of hospital performance that is otherwise too big and complex for traditional technologies. With the use of big data analytics in healthcare, there are numerous benefits, including the potential for saving lives. When used in healthcare, it can help avoid epidemics, cure disease, save costs, and utilize precise health data from a population.

Few Big data examples in healthcare

Now that you know how important health big data is, let’s look at a few real-world examples of how an analytical approach may help systems run more smoothly, patients receive better care, and people live longer.

  1. Predicting the spread of coronavirus: This is an example of how big data has impacted the global coronavirus problem, one of the most recent and relevant examples in healthcare. The rapid development of COVID-19 vaccinations was made possible by the use of big data analytics in healthcare. Researchers can quickly collaborate to develop new medicines by exchanging information with one another. Additionally, big data in healthcare helped predict the spread of disease by allowing healthcare information to be analyzed more quickly than during previous pandemics.
  2. Electronic Health Records: Of all, one of the most important uses has been the construction and use of electronic health records in healthcare. No longer restricted to a single office, patient records are now available to every doctor in the system, regardless of where they are stored on paper.
  3. Opioid Use Monitoring: With the opioid crisis currently raging, healthcare practitioners’ responsibility is to ensure that they appropriately give these highly addictive prescriptions. You can use big data to track opioid consumption and highlight any potential risk factors for opioid misuse before they occur. Big data can help cut opioid use by 17 percent, according to one study.
  4. Predictive Analytics: Predicting what patients might require before they do is another use of big data applications in healthcare. Patients’ medical information, insurance records, and even test findings can be used to train Big Data algorithms to seek for risk variables that might suggest a future disease. Doctors can use this information to work on preventing the sickness in the first place.
  5. Medical Imaging: Using Big Data methods, you can interpret radiographs as well. There are countless instances and examples of diseases and symptoms, making it easier to find problems that a conventional radiologist might not be aware of.
  6. Good Security and Fraud prevention: Health insurance fraud is much more widespread than it may be. Since the beginning of time, service providers have had to cope with the challenge of dealing with misleading information. You can detect inaccurate claims earlier with the help of big data and cybersecurity. It also protects electronic records by preventing criminals from accessing secret and sensitive information.
  7. Cancer Help: The difficulty in battling cancer is because cancer is challenging to identify, and there is no universal treatment. You can use big data to find a cure for some types of cancer by analyzing patient data. Doctors can use biopsies and lab results to assist them in deciding what the next step should be for patients.
  8. Predict Heart Attacks: Many people die each year due to heart attacks. Using Big Data, healthcare providers may gather information about patients and identify risk factors that could cause a heart attack in the future. Having a system to identify and treat heart-related diseases would save countless lives because many people are unaware that they are in danger.
  9. Patient Trackers: Patients who utilize smart devices will have their data collected and matched with their doctors, thanks to the power of Big Data. Wearable devices like fitness trackers can track physical activity, heart rate, sleep patterns, and more. With Big Data, providers can receive this information and compare it to what they already know. This data can then be uploaded.
  10. ER Visit Prevention: Patients who are at risk of coming to the ER can be treated before an ER visit is necessary because of the collection of Big Data on each patient. The analysis of whether or not a patient can be readmitted after they have previously been examined is a part of this.

Big data may help healthcare businesses improve patient outcomes, save money, and increase efficiency across the board. Big data is a big driving force for Pharma businesses to design and build more innovative treatments and products. Healthcare stakeholders can use big data and predictive analytics to address critical concerns such as readmission rates, high-risk patient care, staffing shortages, medication errors, and much more.

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