The Top 5 Big Data Applications in the Healthcare Industry

Big data has leveraging potential to revolutionize the healthcare sector in many ways. Below are the top 5 big data applications to transform healthcare.

In this modern era of leveraging technology, the enhancement of healthcare sectors is crucial especially during the pandemic of COVID-19. Technological advancements can either make or break the future of healthcare and can control the second wave of coronavirus. One method which can be acquired to make healthcare more efficient, accurate, and affordable is by utilizing big data.

Big data has completely revolutionized the way data is analyzed, managed, and leveraged across numerous industries. Noticeable sectors where data analytics is making prominent changes in healthcare. It is estimated that the global big data in the healthcare market will tend to reach $34.27 billion by the year 2022 at a CAGR of 22.07%. Moreover, big data in the healthcare market is expected to bypass the figure of $68.03 billion by the year 2024.

There is no surprise in saying that big data analytics in healthcare has a life-saving yet positive outcome. Essentially big data refers to an extensive amount of information that is produced by the digitization of everything, that is synthesized and analyzed using certain technologies. Particular health data of population is utilized for the prevention of epidemics, cut down cost, cure disease and so on. Doctors want to develop a better understanding as much as they can and as early as possible about their patients to detect the warning signs of some serious illness as that occurs.

Let us dive deeper into big data challenges, applications, and its bright future in the healthcare sector that demonstrate how an analytical approach can enhance patient care, processes, and can ultimately save lives.

Obstacles When Implementing Big Data in Healthcare

There is no organization in the world that does not face any challenges. Following this ritual, healthcare organizations face numerous challenges that fall into 3 major categories including process and privacy, management, and data aggregation challenges.

Let’s explore more in the sections below.

Process and Privacy Challenges

Policy-related issues need to be addressed once the data is authenticated and accumulated after going through numerous processes. HIPAA regulations request that procedures and policies for the protection and reliability of patient’s information. Task gets complicated by security during transmission, access control, authentication, and other similar rules. This issue is solved to a certain extent by cloud service providers. Indeed, most noticeably Amazon AWS provides cloud services that follow Protected Health Information(PHI) and HIPAA.

Management Challenges

Realizing the use-cases of big data in healthcare analytics asks organizations to adjust their methods of operating businesses. Data scientists, along with IT staff are required to have a particular skill set in order to run analytics. Few organizations might struggle with the thought of having “rip and replace” much of their infrastructure. However, cloud services alleviate some of these major concerns. Time might be required to administrators and physicians before they start trusting forthcoming unseen advice provided by big data.

Data Aggregation Challenges

Financial data of patients are spread across numerous hospitals, administrative offices, payors, file cabinets, and government agencies. A lot of planning is required for the collaboration of data producers with the new producing data. Moreover, every organization is required to develop a better understanding of the formats and types of big data they aim to analyze. The accuracy and quality of data are required to be established and maintained looking beyond the issue of the format in which they are stored. This requires data governance along with data cleansing. Organizations must ask themselves some questions such as have the data recorded accurately and efficiently? Or does it possess errors?

5 Unpredictable Big Data Applications In Healthcare

The leveraging potential of big data is reshaping the landscape and dimensions of numerous sectors, especially healthcare in an unpredictable and unbelievable manner. Let’s dive right into the top 5 applications of big data in healthcare.

1. Predictive Analytics in Healthcare

For two years in a row, predictive analytics is considered one of the biggest business intelligence trends but the potential applications bypass businesses and can go much further in the future. A United States research collaborative, Optum Labs has collected EHRs of more than 30 million patients to develop a database for the purpose of predictive analytics that enhances patient care. Assisting doctors and making data-driven decisions accurately and efficiently is the main goal of online business intelligence in healthcare. This is certainly helpful in case patient encounters having complex medical histories and suffering from numerous diseases. Innovative business intelligence tools and solutions are capable enough to predict risks and provide useful pieces of advice.

2. Security Enhancement and Reduce Fraud

Studies have depicted that 93% of health organizations have faced data breaches recently. Personal data is highly profitable yet valuable in the black market. Any data breaching activity would have drastic consequences. Considering that fact, organizations started the utilization of big data analytics to fight a strong battle against security theft and fraudulent activities. Centers for Medicare and Medicaid Services pledged that they would combat over $210.7 million in fraud within a year. Thankfully, Big data sufficiently combat security issues and organizations are becoming more vulnerable than they were previously. Technological advancements such as firewalls, antivirus software, and encryption technologies enhance security features and enhance identity verification solutions.

3. Suicide and Self-Harm Prevention

Almost 800,000 people die every year and 17% of the total world population is harming itself during their lifetime. Concerning the increasing suicide and self-harm rate, big data is making positive impacts in healthcare. Healthcare institutions are utilizing data analysis for the identification of individuals who are prone to self-harm or suicide. Speaking of the matter, a senior investigator, MD, and MPH at Kaiser Permanente Washington Health Research Institute, Gregory E. Simon, claimed “We have concluded that we can utilize electronic health record data in association with other tools for the accurate identification of those people who are at high risk for suicide death or self-harm. ”

4. Integration of Big-Style Data With Medical Imaging

In the United States, approximately 600 million imaging procedures are performed every year as medical imaging is very crucial. Manually storing and utilizing images are expensive both in terms of both money and time. Radiologists are required to examine each image individually while hospitals store them for numerous years. Big data analytics for healthcare can revolutionize the way medical imaging is executed. By the analysis of hundreds and thousands of images, certain algorithms are developed for the identification of specific patterns in pixels and then convert them into numbers to assist physicians with diagnosis. In the near future, radiologists will only analyze the algorithm’s outcook instead of having a look at images.

5. Big Data Might Just Cure Cancer

President Obama came up with the Cancer moonshot program before the end of his second term, which is a very interesting example of big data utilization in healthcare. This program had the goal to achieve 10 years’ worthiness of progression to prevent curing cancer halfway. Medical researchers can utilize an enormous amount of data for the planning of treatments and keep track of the recovery rate of cancer patients for the analysis of trends that have a high rate of success in this world. For instance, researchers can examine tumor samples in biobanks that are associated with patient treatment records. This data assists to cure certain types of lung cancer and can lead to unexpected advantages, such as finding that antidepressant called Desipramine.

The Bright Future of Big Data in Healthcare

Perhaps, prevention is better than cure. Big data helps to draw a comprehensive picture of patients by utilizing healthcare data analytics and key performance indicators. Similarly, the executives of industrial and commercial sectors claimed that their big data initiatives have been transformational, successful, and revolutionary, however, the outlook of big data in healthcare is even more exciting in the upcoming years.

In the sections below are few areas where big data is doomed to revolutionize healthcare.

Machine Learning

The most crucial component of artificial intelligence is majorly dependent on big data to help physicians for the health improvement of patients. IBM along with the Watson Health computer system is currently associated with Memorial Sloan Kettering Cancer Center, CVS Health, and Mayo Clinic. Thanks to the emerging Know Your Patient (KYP) services that boost healthcare identity verification solutions and services. The duo of big data analytics and machine learning multiplies the capabilities of health and patient care.

Precision Medicine

National institutes of health envision enrolling one million people in providing their health information in their “All of Us” research program which is relatively the NIH Medicine initiative. According to NIH, initiatives aim to develop a better understanding of a person’s environment, genetics, and lifestyle which assists to determine the best approach for the prevention and curing of disease. The long-term aim of the Precision Medicine Initiative is to indulge precision medicine in all sectors of healthcare on a very large scale.

Wearables and IoT Sensors

As discussed above, big data has unpredictable potential to completely transform the healthcare sector and enhance patient care. In the upcoming years, wearable devices or sensors will assist in providing direct, real-time feed to the electronic health record of patients, which permits medical staff to monitor and consult the patient either remotely or face-to-face.

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