Health Care Analytics: Definition, Impact, and More

As much as data has revolutionised the financial, marketing, and tech industries, it has also profoundly altered the health care field. Health care 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 health care 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 health care analytics.

What is health care analytics?

Health care 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 health care industry. Health care analytics is not only used to benefit health care organisations 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 records for a set period.

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.

Predictive analytics in health care

Predictive analytics uses 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 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 health care

Prescriptive analytics uses historical data to identify an appropriate course of action. In the health care 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 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 benefits 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, 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

Health care analytics salary and job outlook

As a combination of 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 salary

Those working in health care analytics can expect a higher-than-average salary. According to Glassdoor, the average salary for a health care analyst in India is ₹4,43,458 as of February 2023 [2]. Similar positions in industries outside of health care might possess similarly high salaries. Data scientists in India, for instance, make an average salary of ₹6,70,000 during the same period, according to Glassdoor [3].

Health care analytics jobs

The job outlook for those working in health care analytics is very positive. According to the India Brand Equity Foundation, the health care market in India is estimated to reach 132 billion USD in value by 2023. The Indian government is pouring resources into the health care sector to boost infrastructure with plans to launch a credit incentive programme valuing ₹500 billion [4]. With the expansion of the health care industry in India continuing at a fast pace, there is likely to be growth in related jobs such as health care analytics.

Health care data analytics: Getting started

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

1. Get qualified.

Employers typically expect those looking to enter the field of health care 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, mainly 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.

Health care 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 health care 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 health care analytics field.

4. Learn more about health care.

Health care analytics is an applied form of data analytics. It 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 understand the tools and processes required to undertake data analysis and the unique concerns of the health care industry. 

Whether you opt 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

A career in health care analytics requires a grasp of both data analytics and health care. You might consider taking a flexible online course to better understand either one (or even both). Google’s Data Analytics Professional Certificate, such as data visualisation and R programming, will have them job-ready in less than six months.