What is Biomedical Informatics?

Posted on Jun 30, 2012 in Biomedical Informatics | No Comments

The American Medical Informatics Association (AMIA) define Biomedical Informatics as,

“…all aspects of understanding and promoting the effective organization, analysis, management, and use of information in health care. While the field of medical informatics shares the general scope of these interests with some other health care specialties and disciplines, medical informatics has developed its own areas of emphasis and approaches that have set it apart from other disciplines and specialties. For one, a common thread through medical informatics has been the emphasis on technology as an integral tool to help organize, analyze, manage, and use information. In addition, as professionals involved at the intersection of information and technology and health care, those in medical informatics have historically tended to be engaged in the research, development, and evaluation side, and in studying and teaching the theoretical and methodological underpinnings of data applications in health care.”

Bernstam, Smith and Johnson in their 2010 article discuss why biomedical informatics is difficult to define and have proposed a definition that is grounded in theory.

They state in their paper that “informatics is the science of information, where information is defined as data with meaning. Biomedical informatics is the science of information applied to, or studied in the context of biomedicine. Some, but not all of this information is also knowledge”.

Moving past the definition, the key challenge in the domain is being able to formulate what constitutes a problem in Biomedical Informatics. In the abstract sense, problems in BMI require “meaning” or context to be considered. The problems may utilize tools from other disciplines such as computer, cognitive and other information sciences. In many ways, these problems may be considered to be “more difficult than problems where manipulating data without regard for meaning is sufficient” (Bernstam et al.). I would argue that problems in the domain deal with a different difficult problem – processing contextualized data). Aside from minor differences of opinion, it is an interesting domain to do some application-oriented research.

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