“Biomedical informatics (BMI) is the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, driven by efforts to improve human health.” [1]
“…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.” [2]
Figure 1: The scales of biomedical entities, ranging from molecules to populations.

The landscape of biomedical informatics (BMI) is defined by four components (Figure 1): (1) biomedical entities—ranging in scale from molecules within biological systems to groups of people within social systems (2) people who have information needs (including researchers, healthcare workers, and patients), (3) information technologies and computational methods, and (4) biomedical data, information, and knowledge. As illustrated in Figure 2, BMI bridges the gap between data, information, and knowledge and those who need this information and knowledge to support decision making, problem solving, and research.

Figure 2: The landscape of biomedical informatics is defined by biomedical entities (left), people (right), information technologies and methods (top), and biomedical data, information, and knowledge (center).

BMI addresses all phases of problem solving

Activities of BMI researchers and practitioners can be mapped to three phases of design-based problem solving:

(1) Understanding users’ needs and the context of information use

Before problems can be addressed, they must be understood. Work in this category seeks to understand users’ information needs and workflows, their current tools and technologies, and the social and organizational context of information use.

(2) Developing and implementing technologies, systems, and resources

BMI develops solutions to address gaps between the information needs of users and the tools available for processing, managing, storing, manipulating, retrieving, and transmitting data and information. Examples of work in this category are:

  • Developing computational methods to help find meaning in data
  • Designing information systems to provide researchers and clinicians with information relevant to their current task
  • Developing information resources that integrate disparate data to make the data more useful
  • Developing systems that capture patient data in ways that are secure, support patient care, and are suitable for biomedical research

(3) Evaluating and refining technologies, systems, and resources

BMI is a scientific discipline, and therefore inquiry is guided by the development and testing of theories. BMI draws upon many component sciences, including information science, computer science, statistics, organizational science, and cognitive science.

As a science, the object of study in BMI is information. BMI also incorporates some elements of engineering, where the focus is building software tools.

BMI spans both foundational and application domains

Work in BMI may applicable to foundational research, an application domain, or both. Foundational work focuses on the study of information itself, as well as its representation and manipulation. Work in foundational domains is intended to be applied to different types of problems and in different contexts. Examples include research in methods of knowledge representation, data mining, modeling, and simulation.

Other work is focused on solving information problems in specific contexts of biomedical research or healthcare delivery. These application domains include bioinformatics, clinical informatics, public health informatics, consumer health informatics, imaging informatics, nursing informatics, and dental informatics.

BMI also contributes to research linking biomedical research and healthcare delivery. BMI supports this “translational research” by developing systems that make information and knowledge produced by investigators working on basic laboratory or clinical questions available to those who can apply it in ways more directly relevant to improving human health.

BMI activities are united by a set of themes

As an interdisciplinary field, BMI is broad in scope and varied in types of activities. But because BMI centers on making biomedical information useful, activities within different domains are united by common themes. These include:

  • The use of standards for representing data, information, and knowledge
  • The need to integrate heterogeneous data or disparate datasets
  • The “secondary use” of data that was originally collected for a different purpose.

References

[1] C A Kulikowski et al., “AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline,” Journal of the American Medical Informatics Association, vol. 19, no. 6, pp. 931–938, November 2012.

Source of the current consensus definition of biomedical informatics, plus core competencies for graduate programs. Based on work of the AMIA Academic Forum Committee.

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[2] E V Bernstam, J. W. Smith, and T. R. Johnson, “What is biomedical informatics?,” Journal of Biomedical Informatics, vol. 43, no. 1, pp. 104–110, February 2010.

Defines information as data + meaning, and explores the implications of this definition for the discipline of biomedical informatics.

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Additional reading

C P Friedman, “A ‘Fundamental Theorem’ of Biomedical Informatics,” Journal of the American Medical Informatics Association, vol. 16, no. 2, pp. 169–170, March 2009.

Proposes that the work of informatics is to create and support information resources such that “a person working in partnership with an information resource is ‘better’ than that same person unassisted.”

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C P Friedman, “What informatics is and isn’t,” Journal of the American Medical Informatics Association, vol. 20, no. 2, pp. 224–226, March 2013.

Provides three metaphor-driven perspectives to define biomedical informatics, then uses these perspectives to distinguish biomedical informatics from other work using computers and information technology in the domains of healthcare and health-related research.

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W Hersh, “A stimulus to define informatics and health information technology,” BMC Medical Informatics and Decision Making, vol. 9, no. 1, December 2009.

Defines a myriad of terms associated with biomedical informatics and health information technology.

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E V Bernstam et al., “Synergies and distinctions between computational disciplines in biomedical research: perspective from the Clinical and Translational Science Award programs:,” Academic Medicine, vol. 84, no. 7, pp. 964–970, July 2009.

Distinguishes between operational IT, research IT, computer science, and biomedical informatics in the context of performing clinical and translational research.

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R A Greenes and E H Shortliffe, “Commentary: informatics in biomedicine and health care,” Academic Medicine, vol. 84, no. 7, pp. 818–820, July 2009.

Response to article by Bernstam et al., arguing that the authors emphasized the use of computers and information technology systems within biomedical informatics, while neglecting to portray the foundation of biomedical informatics as interaction of information, people, and technology systems.

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S H Woolf, “The meaning of translational research and why it matters,” JAMA, vol. 299, no. 2, January 2008.

Calls attention to the use of the term “translational research” to describe two very different activities: (1) translating the findings of basic science to clinically-based research, and (2) translating research into clinical practice.

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A A Kon, “The Clinical and Translational Science Award (CTSA) consortium and the translational research model,” The American Journal of Bioethics, vol. 8, no. 3, pp. 58–60, June 2008.

Discusses the many forms of translational research and the role of Clinical and Translational Science Award (CTSA) programs.

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