This special issue of JAMIA focuses on data sciences. But what is the relationship between data sciences and health (or biomedical) informatics?
The fundamentals of the field of informatics have been constant – we are investigators, educators, and practitioners who collect important health information. We organize, analyze, and convert data into knowledge, and then we use technology to apply that knowledge to improve health and health care. While our field has been called different names through the years – medical information sciences, biomedical informatics, health informatics – the fundamental science and its application in health and health care have been consistent.
Informatics professionals as a group are composed of a diverse collection of individuals with diverse areas of expertise. Take any aspect of health or health care, and the informatics applications span 360 degrees of distinction. While there are distinct communities, informatics is more than just the sum of its parts; it is a core set of knowledge applied by these individuals to solve their unique problems. Nurses, public health officers, imaging specialists, basic scientists, and others: informatics professionals have highlighted their diverse interests in describing expertise in nursing informatics, public health informatics, and other areas of investigation. Others describe their area of interest in consumer informatics, clinical research informatics, or translational bioinformatics. The distinctions help to identify the people for whom and the areas in which we use informatics to improve health and health care and provide a sense of community.
How you define the relationship between informatics and data science depends on your perspective. Individuals who started their work in clinical care or informatics see the powerful tools and analytic techniques of data science as part of informatics that help researchers and informatics practitioners understand the data more effectively and leverage that for patient care. Individuals who started their careers in the computational work of statistics or computer science look to informatics as a subset of data science that helps them focus attention on collecting data and understanding how to apply knowledge gained from data science techniques to improve care.
Data science is yet another descriptive distinction applied to differentiate work with health data. When it comes to data science, some would argue that informatics professionals have been doing it all along, and that informatics and data science are the same thing. Others see data science as the overarching field, which informatics, statistics, and computer science all support. Still others would argue that biomedical data science is a subfield of expertise in informatics that includes the collection and organization of data, the analysis of data to transform it into actionable knowledge, and the application of knowledge to specific clinical problems.
AMIA’s membership of 5400 informatics professionals includes many who consider themselves data scientists, and this designation is accurate. The labels are less important than the way that these professionals apply their expertise. Informatics professionals were leaders in data science long before the label was applied. And this expertise transcends the domains of research or the professional affiliations in which we work.
But in defining health informatics and its relationship (and overlap) with data science, we have a unique opportunity. We can use real experience and real data to help us define – and understand – the relationship between data science and informatics.
One important way that we see the relationship between data science and informatics is through the acknowledged shared core competencies. A key strategic initiative for AMIA in 2018 will be to update the core skills, competencies, and knowledge that informatics professionals possess. In doing so, we will operationally define informatics and the relationship between informatics and data science. This includes refreshing not only the clinical informatics core content for board-certified physicians, but also the accreditation standards for informatics programs. As we develop educational programs in AMIA, the overlap between informatics and data science will be incorporated. Other scientific fields have corpora of knowledge that define them; these activities in 2018 stand to provide the same.
So, what is your perspective? From data science to informatics or the other way around – tell me what you think. AMIA has made this JAMIA data science issue freely available (no subscription required) so that researchers and scientists can delve into the issues, learn about data science in the context of informatics, and share the information with friends and colleagues. Together, the communities of informatics and data science are strongest when we can leverage our different perspectives for the one goal of using information technology to improve health and health care. Tell me your thoughts on data science and informatics. Reach me at fridsma@amia.org and on Twitter at @fridsma.