The Promise of Big Data in Healthcare

The Promise of Big Data in Healthcare

The history of big data in healthcare dates to the 1500s, during the time of the bubonic plague, but the weekly disease mortality reports, analyzed and published by John Graunt in 1663, pale in comparison to the enormous amount of health-related information available today.1, 2 Approximately 153 exabytes of healthcare data were generated in 2013. (One exabyte equals a billion gigabytes!3) This number grew to more than 2,000 exabytes in 2020.4 Healthcare data makes up 30%—projected to rise to 36% by 2025—of all the world’s generated data.5 

The COVID-19 pandemic has helped to expedite the adoption of new technology and big data in healthcare, whether it involves letting patients make vaccination appointments online or documenting vaccines administered and uploading the data to regional registries. Currently, healthcare organizations use big data and advanced technologies such as artificial intelligence (AI) and machine learning (ML) for telemedicine, to check patient symptoms and to make hospitalization forecasts that can assist in decision-making and operational strategies.6

Keep reading to learn how big data is used in the healthcare industry, what the challenges and future trends are, and how you can be at the forefront of this exciting field.

What is Big Data in Healthcare?

The term “big data” means a very large volume of structured and unstructured business data. This immense amount of information can be analyzed to extract insights that can lead to better-informed decisions and more sound business strategies.2

Where Does Healthcare Data Come From?

Health-related information comes from a wide variety of sources, such as:


This includes public health surveys, questionnaires and interviews.

Medical Records

Diagnoses, lab tests, procedures and other services are collected in a patient’s medical record. Most of this is now included in their electronic health records (EHR).

Claims Data

This administrative data includes electronic data from appointments, bills, insurance information and patient-doctor communication.

Vital Records

Births, deaths, marriages, divorces and fetal deaths are collected by the National Vital Statistics System.


Public health surveillance is the continuous collection, interpretation and dissemination of data used to help prevent and control injury and disease. Agencies such as the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) maintain databases and online reporting systems, such as disease registries.

Peer-Reviewed Literature

Journal articles that go through critical evaluation become part of the large collection of health data, including research, studies and surveys.7

Two other major sources of big data in healthcare are omics studies (genomics, etc.) and the Internet of Medical Things (IoMT). IoMT includes wearable biosensors, devices that track health and fitness, clinical devices that monitor a patient’s vital signs and other types of clinical instruments.8,6  

How is Big Data Used in Healthcare?

Big data in healthcare brings clarity and insight into various areas, such as product development, patient outcomes, operational efficiency and innovation.2

Healthcare professionals use big data to accomplish many important tasks:

Predict Patient Risk for Disease

Hospitals can use big data and AI to predict which of their patients may be at greater risk of certain kinds of diseases. They can also use this technology to project the duration of surgical cases and detect cases of sepsis.6

Improve Patient Monitoring and Engagement

The use of AI, ML and big data in healthcare brings new digital health capabilities to medical facilities for enhancing the surveillance monitoring of patients for better outcomes. Mobile apps and smart devices let patients track their medical data, which can be uploaded and stored in the cloud to provide a more complete picture of their health. Potential health risks can be detected. Patients’ data can be handled more holistically by doctors, and with EHRs, all health information is stored in an easy-to-access central location.2,6

Focus on Proactive Diagnoses and Treatments

With extensive health data for patients, health care providers (HCP) can be proactive in their diagnostics and treatment for a greater focus on wellness, rather than merely responding to symptoms.6

Speed Up Product Development

Clinical trials can take a long time but doing digital studies and being able to generate large amounts of data can greatly shorten the discovery phase before scientists start human clinical trials.2,6

Make Better-Informed Operational Decisions

Collecting data and gaining insight into daily operations enables hospitals to adapt their workflows, manage staff and improve patient care. Big data allows for more strategic planning.2,6

Prevent Unnecessary Emergency Room Visits

Sharing patient data among healthcare providers and having this information readily available can help to prevent unnecessary use of visits to emergency department facilities. If certain testing has been done at a different facility, for example, it may not be needed again in the ER. It may also be possible for a patient to use telemedicine for a diagnosis, avoiding a trip to the ER altogether.2

The Biggest Challenges of Big Data in Healthcare—and Possible Solutions

The primary challenges of using big data in healthcare are the questions of security, interoperability and resources.


With patient reports, digital health records, clinical data, electronic health reports and online data, the need to secure sensitive health data and other personal information remains a key industry concern. Big data must be protected from hackers and other malicious users. Healthcare organizations are now looking to Blockchain technology for this protection. Using a decentralized, distributed application, smart contracts and an InterPlanetary File System (IPFS), healthcare data can be securely uploaded, accessed and stored.10


The ability of IoMT devices and other systems to exchange information is a key challenge in the healthcare industry. This is often due to a lack of standards between systems and vendors. The Cures Act and the CMS Interoperability and Patient Access Final Rules dictate guidelines for health data sharing and interoperability. Their goal is a more seamless nationwide exchange of health information and easier access to medical records for patients.11,12,13


Healthcare organizations often lack the necessary infrastructure to collect, process and maintain huge amounts of data. Fortunately, cloud providers now offer data management and storage options.6

The Use of Big Data in Healthcare—Future Trends

According to the Healthcare Information and Management Systems Society (HIMSS), these are the top trends when it comes to big data in healthcare. 

Expanding Categories

Volume of data, velocity and variety—but also value and veracity. Private health data is being collected more quickly and efficiently, from a great variety of sources. This makes its security even more important, as it has such tremendous potential value in the marketplace.14

Data Lakes

This term refers to allowing different points of collection and access, but securely maintaining the essential raw data.14

Predictive Analysis

Predictive analysis, which relies on big data and AI, allows healthcare providers to make important decisions for both patient care and operations, for better outcomes and cost savings.14

Diverse Data 

Healthcare equality is a hot topic and data plays an important role. Big data enables analysis of diverse information from many different sources so that social and socioeconomic determinants that impact health and healthcare can be considered.14

Big Data and AI

Effective AI depends on big data so that the technology can continue to grow and provide immense value to patients and healthcare providers.14

The Need for Big Data Professionals

With the exponential growth of digitalization and big data in healthcare, there is a strong demand for data professionals who know how to harness large amounts of information and turn it into actionable data that’s of value for decision-makers. The U.S. Bureau of Labor Statistics projects that the job growth for operations research analysts will be 23% between 2021 and 2031—much higher than other professions.9

Be on the Leading Edge of the Big Data and Healthcare Revolution

There is tremendous opportunity in the healthcare industry—but only if you have the right data science skills. With the EmergingEd online data science courses, you can gain the knowledge and real-world skills you need to thrive in this rapidly changing and lucrative field. Classes include Machine Learning Foundations and Frameworks, Machine Learning and Industry and Machine Learning Cases. These intensive classes, designed for busy professionals, will give you the in-depth knowledge and skills that are in demand.



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