Some terms withstand the test of time, and I am pleased to note that "informatics" fits into that category. The word traces its origins back to the 1960s, and the importance of the discipline has withstood the test of time. As with all fields, the leading edge has changed substantially, but the core function and definition of the field - the use of data, information, and knowledge to improve human health - has not.
Like many fields, informatics has seen the emergence of areas of work that overlap with its work, in essence that provide semantic drift not only from the core definition of informatics but also the description of work that rightfully belongs to it. I am referring to some of the emerging "hot topics" in recent years, such as data science, data analytics, and precision medicine. I suspect that some may argue these are different from informatics, but I would rebut that they really fit under the broad umbrella of informatics.
I also believe these new sub-disciplines need to prove their work, just as informatics has (or in some cases has not). Like most established disciplines, informatics has a long trail of science. Not all of it is strong methodologically, particularly the portion that evaluates systems in the real world. But we can point to techniques and implementations that have been studied enough to demonstrate where they do and do not work [1-4]. Informatics also provides a good deal of experience and perspective in having tried to address some of what these new sub-disciplines are trying to accomplish.
The current hot topic is precision medicine [5-6]. While I share the excitement and recognize its potential, I also know that it is still an unproven science. In other words, there are still few "products" of precision medicine that demonstrated any large-scale success. This does not mean precision medicine will not have such benefit, or that further research should not be pursued. But we also need to look for its results, especially those that lead to improved health and of outcomes from treatment of disease. The same holds true for the previous hot topic before precision medicine, namely data analytics and other aspects of Big Data.
In the meantime, I would encourage those who are pursuing these emerging areas to find a home in the larger science of informatics. Indeed, those from the informatics community are working in them (myself included), and we should show there is a solid trail of science leading into them and eschew that they are somehow completely brand new.
1. Chaudhry, B, Wang, J, et al. (2006). Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine. 144: 742-752.
2. Goldzweig, CL, Towfigh, A, et al. (2009). Costs and benefits of health information technology: new trends from the literature. Health Affairs. 28: w282-w293.
3. Buntin, MB, Burke, MF, et al. (2011). The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Affairs. 30: 464-471.
4. Jones, SS, Rudin, RS, et al. (2014). Health information technology: an updated systematic review with a focus on meaningful use. Annals of Internal Medicine. 160: 48-54.
5. Collins, FS and Varmus, H (2015). A new initiative on precision medicine. New England Journal of Medicine. 372: 793-795.
6. Ashley, EA (2015). The Precision Medicine Initiative - a new national effort. Journal of the American Medical Association, Epub ahead of print.