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How Do I Become a Health Care Data Analyst?

April 07, 2022
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Health care and technology are two of the fastest-growing fields in the U.S. It’s no surprise health care data analytics, in particular, is growing at a rapid pace. This relatively new field has an employment rate that is set to grow by 30% over the next ten years, and is expected to reach $31 billion by this year.1,2

With so much room for evolution and growth, it’s not surprising that many professionals and recent graduates are now looking to enter the industry as health care data analysts. But with so many varying job titles and roles, how does one break into the field and how do you know what skills you’ll need for the title you’re taking on?

We’ll explore what highly trained data analysts will need to know, and do, to succeed in the health care industry.

What Do Health Care Data Analysts Do?

At their cores, health care data analysts are translators. They spot the trends and patterns in large datasets then translate those numbers into plain English for key stakeholders and decision-makers.

By allowing their organizations to make informed decisions, health care data analysts can help health care facilities and organizations improve care methods, reduce costs and help hospitals and health care facilities run more efficiently.

If this is the industry you’re looking to enter, it’s best to look at hospitals, private practices, diagnostic centers, insurance companies and government health departments as a starting point. On a day to day basis, you’ll be expected to:

  • Gather data from a wide range of sources, including database management systems
  • Arrange and manage vast datasets
  • Study the data to discover patterns and trends
  • Translate data from complex models into plain English
  • Provide detailed reports and give presentations about their observations
  • Suggest changes or optimizations based on those observations

Types of Data They Use

To accomplish these daily tasks, health care data analysts are expected to collect and manage data from medical records, finances, patient surveys and pharmaceutical databases. Here’s how each of these can be used to improve health care at different points in the patient journey:

Pharmaceutical data

These datasets are used to help bolster research and development of production methods as well as the pharmaceutical products themselves. The data they compile and use can help improve clinical trials or advance the development of drugs that can cure diseases like cancer.3

Behavioral data

Behavior and feelings aren’t usually the first thing people think of when they hear Big Data, but this information is crucial to health care. Monitoring behaviors, habits and sentiments can help health care professionals quickly identify and deal with common illnesses and issues related to patients’ routine activities.4

Cost and claims data

This data is more directly related to the business side of health care. It allows analysts to help health care institutions and organizations identify areas to invest in as well as practices where funds and materials are being used improperly or even wasted. On a more personal level, these data analysts can help patients get a better understanding of how their insurance premiums and claims work and identify medical interventions that may be better suited for them.5

Clinical data

This probably is the first thing people think of when they hear “health care data analytics.” This is most likely the oldest form of analytics in the health care industry and it’s almost always linked to improving patient outcomes. However, in the era of electronic health records (EHRs), we now have far more clinical data available and it’s faster and easier for health care data analysts to obtain it. These datasets can be used to minimize risk for patients, boost the quality of care and program AI to identify cancer at a higher rate than humans can.6

What Skills Do They Need?

The core skills that health care data analysts need aren’t very different than those of data analysts in any other sector. Aside from the basic communication, problem-solving and interpersonal skills that are required at nearly every job, you’ll also need to be able to use the following technology and understand/learn the following medical processes:

Cloud computing

Your average health care system handles a lot of data on a daily basis. Processing and storing that data effectively depends largely on the IT infrastructure that the data sits on. Instead of investing in on-site infrastructure and deployments, a much more cost-effective method is cloud computing. On-site databases allow for a bit more control, but when looking for scalable substitutes, health care organizations usually turn to cloud-based solutions. Cloud computing can be used to store EHRs, streamline patient care across multiple physicians, drive medical research and drive data interoperability.7

Data visualization

With mountains of raw data available, it’s hard to know what’s important. That’s why visualization tools have become crucial in the medical industry. Analysts need to use data visualization to bring the most relevant information into the spotlight. This helps medical staff understand analytics results at a faster rate, spot trends and make informed decisions. Health care data analysts create infographics, charts, graphs, timelines, scatter plots and tables to carry out exploratory analysis on large datasets. The software they use includes but isn’t limited to: Tableau, Domo, Sisense, Bold BI and Google Data Studio.8

Machine learning

Handling the amount of raw data that is available in health care can be a daunting task. Analysts can and should use machine learning algorithms like supervised and unsupervised learning and decision trees to help predict data outcomes more accurately. Trained machine learning models can help medical professionals determine treatment for patients and improve their outcomes by identifying solutions from EHRs.9

Database management systems

As technology has become more involved in the medical field, there has been an influx of data points. Analysts need to be able to store the data in ways that make the retrieval of information easier.


Understanding clinical classification codes, such as the International Classification of Diseases (ICD) and the Current Procedural Terminology (CPT), will help you interpret information from medical records.10


A basic knowledge of various medical conditions and how they progress can help you spot patterns, outliers and suggest better methods of care.

Treatment plans

In order to track the quality of care given to patients, analysts will need to know how effective treatment plans are.

Health care-specific tools

Familiarity with EHRs, health care claims and business intelligence tools like UpToDate and Definitive Health care can help you hit the ground running faster.

How To Become a Health Care Data Analyst

Typically, candidates for these roles need at least a bachelor’s degree in a STEM field. Your job opportunities and salary usually improve with a master’s degree in addition to job experience and training in data analytics or health care.

Getting certifications from the American Health Information Management System Association (AHIMA) can also bolster your earning potential and job prospects. Earning the Certified Health Data Analyst (CHDA) certification can prove your expertise and ability to manage, analyze and interpret data accurately and consistently.11

Gain the Skills to Transform Health Care

Marquette’s online Master of Science in Health Care Data Analytics program provides you with the comprehensive knowledge and training you need to help patients and make a difference in their lives and the health care industry. Reach out to an Admissions Advisor to learn more about our interdisciplinary online curriculum, experienced and committed faculty and admissions process.

  1. Retrieved on February 21, 2022, from healthadministrationdegrees.com/programs/certified-health-data-analyst/
  2. Retrieved on February 21, 2022, from healthcarefinancenews.com/news/healthcare-analytics-market-hit-31-billion-2022
  3. Retrieved on February 22, 2022, from iqpc.com/media/1001534/35903.pdf
  4. Retrieved on February 22, 2022, from ncbi.nlm.nih.gov/pmc/articles/PMC7544557/
  5. Retrieved on February 22, 2022, from cdc.gov/workplacehealthpromotion/model/healthcare-cost-data/interpreting.html
  6. Retrieved on February 22, 2022, from bbc.com/news/health-50857759
  7. Retrieved on February 22, 2022, from galendata.com/9-benefits-cloud-computing-healthcare/
  8. Retrieved on February 22, 2022, from demigos.com/blog-post/healthcare-data-visualization/
  9. Retrieved on February 22, 2022, from hevodata.com/learn/health-data-analytics/
  10. Retrieved on February 22, 2022, from medicalbillingandcoding.org/qnas/what-are-the-different-types-of-medical-coding-classification-systems/
  11. Retrieved on February 22, 2022, from ahima.org/certification-careers/certification-exams/chda/