Today the healthcare industry is generating a massive amount of data in the world. The employment rate those people who have the skill set in health information technology and analytics are increasing day by day. There is a certain increase in the importance of data science and analytics professionals due to pandemic situations. From the past few months data science professionals have worked together on COVID 19 data and to build AI/ML models to track the outbreak and to find the information regarding contact tracking, screen application, and vaccine development.
Data and the right tool can improve patient outcomes and reduce health care costs. Healthcare and data science has an intersection where healthcare and data science are an emerging area. Analytics, research, and data science field are emerging and its advantage is increasing. Health data science generally refers to data about biomedical science and public health. The data generally originate from different areas such as organizational studies, clinical trials, medical records, genomic data, etc.
How to Become a Data Scientist in Healthcare?
The majority of data science courses and degrees mainly focus on data science in general and by using foundational skills one can make a data career in healthcare, bioinformatics, genomic science. Data science specialization programs are offered in many universities like masters in health data science eighteen months program by Harvard University. There several courses which are in India as well such as a master of health data science by SRM university etc. the main aim of these programs is to create graduates who can handle huge messy data sets from various sources and make them an analyzable format. It mainly depends on analyzing data using statistical machine learning and drawing insights from it.
And the other skill set required is communication with various healthcare stakeholders. The main job of health data scientists is to communicate with other data scientists to adopt the methods they have used, contact the clinicians to know the disease they are looking for, talk to lab scientists, and with the public and patients to clear the identify the problem.
The biomedical background is not necessary to pursue the master’s program in data science but they must have strong computational and mathematical skills. They must have a strong quantitative background. Mainly students with mathematical or statistics or any related field will be ideal. Healthcare data scientists must have a deep understanding of statistics, linear algebra, and calculus.
Masters in data science receive training in many areas such as quantitative method, regression, statistical, machine learning, and epidemiology methodology. And the main programming languages used in the healthcare data science course are python, R, and SAS.