Health Care Analytics: Definition, Impact, and More

Written by Coursera • Updated on

Health care analytics uses data analysis to improve health care administration and patient care.

[Featured Image]: A woman with long dark hair, wearing a blue sweater. She is sitting in front of her computer,  analyzing data for the health care organization she works for.

As much as data has revolutionized the financial, marketing, and tech industries so too has it profoundly altered the field of health care. Today, health care analytics is used for everything from providing business insights to refining diagnostic tools to improving patient care. 

Here, you will find out more about what health analytics is, learn about its benefits for both health care administrators and patients, as well as how you can get started in this exciting new career opportunity. At the end of the article, you will find suggested online courses specifically designed to teach both data analytics and health care analytics. 

What is health care analytics?

Health care analytics is a subset of data analytics that uses both historic and current data to produce actionable insights, improve decision making, and optimize outcomes within the health care industry. Health care analytics is not only used to benefit health care organizations but also to improve the patient experience and health outcomes. 

Data analytics in health care

The health care industry is awash with valuable data in the form of detailed records. Industry regulations stipulate that health care providers must retain many of these records for a set period of time.

This means that health care has become a site of interest for those working with “big data,” or large pools of unstructured data. As a still-developing field, big data analytics in health care offers the potential to reduce operation costs, improve efficiency, and treat patients.

Read more: What Is Big Data? A Layperson's Guide

Predictive analytics in health care

Predictive analytics is the use of historical data to identify past trends and project associated future outcomes. In the health care industry, predictive analytics has many impactful uses, such as identifying a patient’s risk for developing a health condition, streamlining treatment courses, and reducing a hospital’s number of 30-day readmissions (which can result in costly fines for the hospital).

A 2021 study conducted by a University of Michigan research team illustrates the positive impact that predictive analytics can have on patient treatment. During the study, researchers devised a sensitive blood test that predicted how well patients with HPV-positive throat cancer would respond to specific treatment courses. Overall, the researchers found that their method could predict treatment effectiveness many months earlier than traditional scans [1].

Prescriptive analytics in health care

Prescriptive analytics is the use of historical data to identify an appropriate course of action. In the health care industry, prescriptive analytics is used to both direct business decisions and to literally prescribe treatment plans for patients. As a result, some of the most common uses of prescriptive analytics in health care include identifying a patient’s likelihood of developing diabetes, allocating ventilators for a hospital unit, and enhancing diagnostic imaging tools. 

Benefits of data analytics in health care

Health care analytics offers benefits to health businesses, hospital administrators, and patients. Although it can be tempting to imagine health care analysts working in a virtual  data cloud, the reality is that their work has a tangible impact on how hospitals operate, treatment is provided, and medical research is conducted. 

At a glance, some of the most common benefits of health care analytics include: 

  • Improved patient care, such as offering more effective courses of treatment

  • Predictions for a patient’s vulnerability to a particular medical condition 

  • More accurate health insurance rates

  • Improved scheduling for both patients and staff 

  • Optimized resource allocation 

  • More efficient decision-making at the business and patient care level  

Health care analytics salary and job outlook

As a combination of both health care and data analytics – two of the fastest growing industries – health care analysts can command a higher than average salary in a field that’s here to stay. 

Health care analytics job outlook 

The job outlook for those working in health care analytics is very positive. 

According to the US Bureau of Labor Statistics (BLS), health care occupations are expected to grow 16 percent between 2020 and 2030 for a total of 2.6 million new jobs [2]. During the same period, the BLS projects that jobs for operation research analysts – the category under which data analysts fall – will grow by 25 percent with an average of 10,200 new openings each year [3].

The combined growth of these two industries suggests that the demand for those working in health care analytics will continue to be strong for the foreseeable future. 

Health care analytics salary 

Those working in health care analytics can expect a higher than average salary. According to Glassdoor, for example, the average salary for a health care analyst was $93,896 as of May 2022 [4]. Other positions that those working in health care analytics might possess had similarly high salaries. Data scientists, for instance, made an average salary of $121,018 during the same period, according to Glassdoor [5]. 

Health care data analytics: Getting started

A career in health care analytics begins with acquiring the appropriate credentials, skills and experience. 

1. Get qualified.

Those looking to enter the field of health care analytics are typically expected by employers to have a credential that signals their qualification for the position. While it is possible to land a job without either a certificate or degree, the two most common routes to entry-level positions include: 

  • Obtaining a professional certificate. A professional certificate indicates that you have taken a particular course of study that has equipped you with the appropriate skills for the position. This can be particularly enticing to job seekers or career switchers who don’t have the resources to pursue a four-year college degree, particularly if they are eager to join the field. Google’s Data Analytics Professional Certificate, for example, equips beginners with foundational data analytics skills in just six months. 

  • Obtaining a bachelor’s degree. A bachelor’s degree signals to employers that you have completed several years of dedicated study to a particular field. Some common fields of study for those entering data analytics include mathematics, statistics, and computer science. 

Read more: How to Become a Data Analyst (with or Without a Degree)

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2. Gain the right skills.

Health care analytics requires a mix of both technical skills and personal skills to ensure that you do your job well. Some of the most common skills include the following: 

  • Programming languages, such as Python or R

  • Database tools, including SQL and Excel

  • Data visualization tools, such as Tableau, Excel, and Jupyter Notebooks

  • Problem-solving abilities 

  • Collaboration 

  • Storytelling, particularly as it relates to data 

3. Gain experience.

Employers like to see prior experience on resumes because it demonstrates that the applicant already has some experience doing that job in the professional world. In effect, it can be helpful for those just entering health care analytics to gain prior experience either through an internship, volunteer effort, or a related job.

Though an internship in health care analytics is likely the best option for job seekers, any data analytics or health care internship will likely improve your resume and signal your acquaintance with the field. 

4. Learn more about health care.

Health care analytics is as much about health care as it is about data analytics. As a result, an individual working in health care analytics should strive to not only understand the tools and processes required to undertake data analysis but also the unique concerns of the health care industry. 

Whether you decide to volunteer at a hospital, obtain a health care internship, or take online health courses, expanding your understanding of the health system will only better prepare you for your future role in health care analytics.

Take your next steps with Coursera

A career in health care analytics requires a grasp of both data analytics and health care. To gain a deeper understanding of either one (or even both), you might consider taking a flexible, online course.

Google’s Data Analytics Professional Certificate , such as data visualization and R programming, that will have them job-ready in less than six months.

For those with prior experience, UC Davis’ Health Information Literacy for Data Analytics Specialization prepares learners to transfer their data analysis skills to the complex world of health care. 


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Article sources


EurekAlert. “Blood test promising for predicting response in metastatic HPV-positive throat cancer,” Accessed August 11, 2022. 

Written by Coursera • Updated on

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