Big data has had a big impact on how health care is provided and recieved. Learn more about how data is transforming the field and why it matters.
Health care is awash in valuable data. Every patient, test, scan, diagnosis, treatment plan, medical trial, prescription, and ultimate health outcome produces a data point that can help improve how care is given in the future. Typically, a large amount of data is called “big data” and it’s through this high volume data that some of the biggest possible health advances lie. But, how does big data actually get used in health care and what’s its impact?
In this article, you’ll learn more about what big data is, how it’s used in health care, its benefits, and the jobs centered around it. At the end, you’ll also explore some online courses that can help you get started in the career today.
Big data refers to large data sets consisting of both structured and unstructured data that are analyzed to find insights, trends, and patterns. Most commonly, big data is defined by the three V’s – volume, velocity, and variety – meaning that it has a high volume of data generated quickly and consisting of different data types, such as text, images, graphs, or videos [1, 2].
In health care, big data is generated by various sources and analyzed to guide decision-making, improve patient outcomes, and decrease health care costs, among other things. Some of the most common sources of big data in health care include electronic health records (EHR), electronic medical records (EMRs), personal health records (PHRs), and data produced by widespread digital health tools like wearable medical devices and mobile health apps.
Perhaps the most common source of big data in health care is electronic health records (EHRs), which typically contain a patient’s medical history, demographic information, medications, immunizations, test results, and progress notes. While in the past this information was put down in hand-written files that were easily misplaced, difficult to share, and occasionally illegible, today EHRs allow health care professionals to easily access a patient’s pertinent medical information and provide the best possible care.
Pairing the big data produced by EHRs with advanced analytics techniques like machine learning, medical researchers can create predictive models with various applications, such as predicting post-surgical complications, heart failure, or substance abuse .
Data professionals working in health care use big data for a variety of applications, from simply improving the patient experience to creating complex machine learning models capable of diagnosing medical conditions using x-ray scans. To accomplish these feats, data professionals use analytics to effectively manage and analyze big data to produce insights, identify patterns and trends, and guide decision-making.
The impact of big data in health care is huge, and the market has grown to match it. According to research conducted by Allied Market Research in 2019, for example, the North American market value for big data analytics in health care is projected to reach $34.16 billion by 2025, several times higher than its $9.36 billion valuation in 2017 . Just as big data lays the foundation for big advances in health care, it has also drawn investment for further growth.
Professionals in health care use big data for a wide range of purposes – from developing insights in biomedical research to providing patients with personalized medicine. Here are just some of the ways that big data is used in health care today:
Employing predictive analytics to create machine learning models that can predict the likelihood a patient might develop a particular disease.
Providing real-time alerts to medical staff by continuously monitoring patient conditions within a facility.
Enhancing security surrounding the processing of sensitive medical data, such as insurance claims and medical records.
Big data has the potential to improve health care for the better. Here are some of the most common benefits of using big data in health care:
Better patient care: More patient data means an opportunity to better understand the patient experience and improve the care they receive.
Improved research: Big data gives medical researchers unprecedented access to a large volume of data and methods of collecting data. In turn, this data can drive important medical breakthroughs that save lives.
Smarter treatment plans: Analyzing the treatment plans that helped patients (and those that didn’t) can help researchers create even better treatment plans for future patients.
Reduced costs for patients and health providers: Health care can cost a lot. Big data offers the possibility of reducing the cost of obtaining and providing health care by identifying appropriate treatment plans, allocating resources intelligently, and identifying potential health issues before they occur.
There are many jobs that use big data analytics in health care. Here are some of the most common that you’ll likely encounter as you explore the field:
Health data engineer
Health care data analyst
Health care statistician
Health care has been transformed by the digital revolution and the data its produced. Prepare for your future in the field by taking a flexible, online course through Coursera today.
Google’s Data Analytics Professional Certification teaches the fundamentals of data analysis in just six months. Learn how to process and analyze data, use key analysis tools and create visualizations that can inform key business decisions.
Johns Hopkins Health Informatics Specialization teaches course takers how to tackle health IT and big data the right way by articulating a coherent problem, designing a health informatics solution, and using data retrieval and analysis.
This is your path to a career in data analytics. In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience required.
1,111,817 already enrolled
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Spreadsheet, Data Cleansing, Data Analysis, Data Visualization (DataViz), SQL, Questioning, Decision-Making, Problem Solving, Metadata, Data Collection, Data Ethics, Sample Size Determination, Data Integrity, Data Calculations, Data Aggregation, Tableau Software, Presentation, R Programming, R Markdown, Rstudio, Job portfolio, case study
Gartner. “Gartner Glossary: Big Data, https://www.gartner.com/en/information-technology/glossary/big-data.” Accessed September 6, 2022.
NIH. “Clinical Implementation of Predictive Models Embedded within Electronic Health Record Systems: A Systematic Review, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710328/.” Accessed September 7, 2022.
Allied Market Research. “North America Big Data Analytics In Healthcare Market…, https://www.alliedmarketresearch.com/north-america-big-data-analytics-in-healthcare-market.” Accessed September 7, 2022.
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.