When it comes to jobs, the public health sector offers a variety of employment opportunities that help make a difference to people’s lives. This includes anything from public health nurses and medical administrators to biostatisticians and epidemiologists. However, in recent years, the increasing need for specialists in data science has created a new pathway for those wanting to work within the industry.

Currently, health systems around the world are experiencing a digital revolution, which enables authorities to garner more data than ever before. Subsequently, global health data is measured in trillions of gigabytes. Moreover, it doubles in size roughly every 2 years.

As a result, many are struggling to keep up with the change, to the point where they are not managing or utilising the data effectively. That is where you could come in.

Interested to find out more? Then keep on reading.

What is health data science?

The term Big Data refers to datasets that are so big and complex, they are virtually impossible to be analysed or evaluated by traditional methods. Within public health, it incorporates millions of records which are regularly generated by health care services.

They include genomic data, which is produced in clinical and research settings, along with clinical data that is captured in real-time at the point-of-care. Additionally, it also encompasses health-related data which is generated among the wider population due to technologies like wearable devices and various social media platforms.

Overall, big data is seen as holding the answers to some of the most pressing health challenges currently being faced in the world, including ensuring better patient outcomes, reducing costs and making smarter decisions.

It is a field that draws knowledge from several different areas within public health, including computer science and biostatistics.

How is data science shaping healthcare?

Overall, big data analytics is playing a leading role in enhancing health services, systems and patient outcomes.

Doctors and other medical professionals need patient data that is as accurate as possible to help them make a well-informed decision about the best form of healthcare they can provide.

Health data scientists provide this by collating massive volumes of data and making it readily available in a concise fashion for them to use.

Data analysis tools have a major influence on how we diagnose, prevent, treat and eradicate diseases. They can help to identify patterns across different populations, races and genders, as well as predict when epidemics might break out.

They can also measure how effective current levels of healthcare provision are and identify any areas that need to be improved.

By doing this, they can provide communities with better health outcomes by reducing the cost of treatment, preventing diseases and facilitating faster breakthroughs in terms of biomedical research. Primarily, this is because the tools make the data analysis process a lot quicker and smoother, which therefore enables researchers to develop data-driven solutions much more quickly.

For instance, algorithms based around machine learning can predict if a certain medication is likely to bring the human body back to full health, and over what timeframe. This, in turn, would increase the speed and reduce the cost of bringing approved medications to market.

What does a health data scientist do?

As a career, health data science is fairly new, so as it evolves, new roles are being created on a regular basis.

Within both the private and public health sectors, there is a growing demand for professionals with qualifications and experience in health data science to work in the field of medicine in Australia.

The role can cover multiple stages within the data science pipeline. They can include everything from context, data management and machine learning to data analytics, data modelling and communication.

Typically, these roles involve running complex data analyses, leading and designing research evaluations or studies, managing teams of other data analysts, and advising management and other stakeholders on various aspects of healthcare analytics.

What Skills Should a Health Data Scientist Have?

Health data scientists should be proficient in various programming languages including Python and R. Congruently, they might also need to demonstrate technical skills such as deep learning, visualisation, algorithms, artificial intelligence, statistical modelling and cybersecurity.

Importantly, health data scientists should be very good communicators, as they will need to clearly convey what the data means to senior management and stakeholders – particularly with regards to how it can be used to shape data-driven decisions.

Study Options

If you are interested in pursuing a career in data science within the public health sphere, your best starting point would be to undertake data science programs at institutions like UNSW, or other notable universities.

Once you have graduated, you will be able to pursue opportunities in various health-related avenues including local, national or state government health departments, pharmaceutical companies, health insurance companies, research institutes and, of course, hospitals.