Healthcare Analytics: Definition, Impact, and More

Written by Coursera Staff • Updated on

Healthcare analytics uses data analysis to improve healthcare administration and patient care.

[Featured image] A data analyst is working with healthcare analytics on a computer in their office.

As much as data has revolutionised the financial, marketing, and tech industries, it has also profoundly altered the healthcare field. Healthcare analytics is used today for everything from providing business insights to refining diagnostic tools to improving patient care. 

Here, you will learn more about health analytics, its benefits for healthcare administrators and patients, and 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 data analytics and healthcare analytics.

What is healthcare analytics?

Healthcare analytics is a subset of data analytics that uses both historical and current data to produce actionable insights, improve decision-making, and optimise outcomes within the healthcare industry. Healthcare analytics is not only used to benefit healthcare organisations but also to improve the patient experience and health outcomes.

What is the role of data analytics in healthcare?

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

This means that healthcare 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 healthcare offers the potential to reduce operational costs, improve efficiency, and treat patients.

Predictive analytics in healthcare

Predictive analytics uses historical data to identify past trends and project-associated future outcomes. In the healthcare 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 30-day readmissions (which can result in costly fines).

A 2021 study conducted by a University of Michigan research team illustrates the positive impact of predictive analytics 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. The researchers found that their method could predict treatment effectiveness many months earlier than traditional scans [1].

Prescriptive analytics in healthcare

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

Why is data analytics important in healthcare?

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

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 

  • Improved scheduling for both patients and staff 

  • Optimised resource allocation 

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

Healthcare analytics salary and job outlook

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

Healthcare analytics salary

Those working in health care analytics can expect a higher-than-average salary. According to Glassdoor, the average annual salary for a healthcare analyst in India is ₹4,35,000 as of July 2025 [2]. Similar positions in industries outside of healthcare might possess similarly high salaries. Data scientists in India, for instance, make an average salary of ₹6,94,530 during the same period according to Glassdoor [3].

Healthcare analytics job outlook

The job outlook for those working in healthcare analytics is very positive. According to the India Brand Equity Foundation, the healthcare market in India is estimated to reach 193.59 billion USD in value by 2032 [4]. The Indian government is pouring resources into the healthcare sector to boost infrastructure, with plans to launch a credit incentive programme valued at ₹50,000 crore (6.8 billion USD) [4]. With the expansion of the healthcare industry in India continuing at a fast pace, there is likely to be growth in related jobs such as healthcare analytics.

What is the future of healthcare analytics?

Several technological innovations are driving the future of healthcare analytics. At the centre of it all is the advancement of artificial intelligence (AI) and machine learning. AI-powered predictive analytics can not only identify patients at risk of developing certain conditions with increased accuracy, but it can also help streamline workflows by forecasting staffing needs and patient demands. Using AI to automate data analysis and processing to provide insights to physicians ensures the efficiency of workflows and the accuracy of diagnoses. AI-driven analytics, combined with real-time data collection from wearable devices, will allow healthcare professionals to continuously monitor patients and make informed decisions about their health, improving patient outcomes through personalised care plans. 

Healthcare data analytics: Getting started

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

1. Take a relevant healthcare analytics course.

Employers typically expect those looking to enter the field of healthcare analytics to have a credential that signals their qualification for the position. Whilst 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 degree: A bachelor’s degree or advanced degree in a relevant field signals to employers that you have completed several years of dedicated study to gain the skills needed to perform job responsibilities successfully. Some common fields of study for those entering data analytics include economics, mathematics, statistics, finance, and computer science.

  • Obtaining a Professional Certificate: This is another way to demonstrate job-ready skills. 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 university degree, especially if they are eager to join the field. For example, Google’s Data Analytics Professional Certificate equips beginners with foundational data analytics skills in just six months.

2. Gain the right skills.

Healthcare analytics requires a mix of technical and human skills to ensure you do your job well. Some of the most common skills include the following: 

  • Programming languages, such as Python

  • Database tools, including SQL and Excel

  • Data visualisation tools, such as Tableau and Excel

  • 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 healthcare analytics to gain prior experience through an internship, volunteer effort, or a related job. This can also be a great way to build your network and learn from more experienced professionals. Working on projects that use data analytics skills, such as data visualisation or data analytics software, can set you up for success in positions in the healthcare analytics field.

4. Learn more about healthcare.

Healthcare analytics is an applied form of data analytics. It is as much about healthcare as it is about data analytics. As a result, an individual working in healthcare analytics should strive to understand the tools and processes required to undertake data analysis and the unique concerns of the healthcare industry. 

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

Explore healthcare data analytics on Coursera

A career in healthcare analytics requires a grasp of both data analytics and healthcare. You might consider taking a flexible online course to better understand either one (or even both). The Google Data Analytics Professional Certificate, which explores topics such as data visualisation and R programming, is designed to have you job-ready in less than six months.

Article sources

1

EurekAlert. “Blood test promising for predicting response in metastatic HPV-positive throat cancer, https://www.eurekalert.org/news-releases/596395.” Accessed 8 July 2025.

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