Graduate Program in Biomedical Informatics
What Is Biomedical Informatics?
Biomedical Informatics is the interdisciplinary science that deals with biomedical information, its structure, acquisition and use. "Biomedical" is used here in its broadest sense, to include research, education, and service in health-related basic sciences, clinical disciplines, and health care administration. Biomedical informatics is grounded in the principles of computer science, information science, cognitive science, social science, and engineering, as well as the clinical and basic sciences. Biomedical informatics encompasses a spectrum similar in scope to the sequence from mathematics to physics to engineering. It includes scientific endeavors ranging from theoretical model construction to the building and evaluation of applied systems.
Key research areas include: (1) understanding how and why researchers and practitioners use information to accomplish their objectives; (2) modeling structures for representing data and information that make relationships between concepts and terms explicit; (3) developing and evolving computer-assisted decision support systems to improve clinical practice, biomedical research, education, and administration; (4) understanding and addressing related workflow, change management, communication, and human-computer interface issues; and, (5) developing methods for evaluation of models and systems, including health services research, data mining and limiting retrieval to context.
Early academic units for "medical" or "health" informatics tended to focus on application of informatics to support clinical practice and clinical research; often, at other institutions, academic units devoted to bioinformatics and clinical informatics evolved separately. In establishing the Department of Biomedical Informatics at Vanderbilt, we added the "bio" to "medical" to signal our intent to establish a core of the informatics competencies covering the intersections relevant to all of biomedicine. The idea is to gain leverage across the entire mission of the medical center and affiliated portions of other academic units (colleges) at Vanderbilt, in order to solve problems related to clinical care, biomedical education, biomedical research, and administration.
Figure 1: An informatics-centric view of the intersections and overlap among the biological sciences, health services research, and information analysis and presentation. It shows that bioinformatics includes a core of biomedical informatics techniques that can be applied to both biological science and health services research, together with its own applied computation and statistics techniques. Similarly, "clinical" or "health" informatics reuses that core, while adding clinical epidemiology, etc. The common core leads naturally to the common information foundation needed for rapid translation between bench and bedside. A "networked" or "web-like" organization structure is needed to provide a critical mass of people to nurture growth in each of the core disciplines of biomedical informatics, statistics and computation, while at the same time providing separate concentration on application to the biological sciences, health services research and translation between the two.
A Brief History of Biomedical Informatics as a Discipline
In Germany, the first professional organization for informatics, currently known as the Deutsche Gesellschaft fur Medizinische Dokumentation, Informatik und Statistik, was founded by Gustav Wagner in 1949. The first appearance of medical informatics (broadly defined to include "biomedical informatics" as well as "health informatics" as explained in this page) as a term ("Informatique Medicale") occurred in France during the 1960s. Specialized university departments and training programs for medical informatics were created as early as the 1960s in France, Germany, Belgium, and The Netherlands. During the 1970s, dedicated medical informatics research units also appeared in Poland, and in the U.S. (the identifying term being "Informatiyki Medycznej", and "Medical Informatics" respectively). Today the International Medical Informatics Association has 40 dues-paying national associations as members covering a spectrum of economic development, from the least industrialized nations (e.g., Bosnia, Cuba, Nigeria), to the most highly-developed ones (e.g., the U.S., Switzerland, Canada, France, Germany, the U.K., and Japan).
Development of high-quality medical informatics research, education, infrastructure and applications, has been a specific goal of both the European Union (e.g., the Advanced Informatics in Medicine program), as well as of the U.S. This latter commitment has been implemented mainly through NLM, an NIH branch that since the mid-80s has been funding medical informatics education at the graduate and post-graduate levels at 12 "Centers of excellence"). The Association of American Medical Colleges (AAMC) has recently issued recommendations regarding the importance of and the approaches needed for successful introduction of biomedical informatics education in US medical schools. In 1990 Robert Greenes and Ted Shortliffe argued that medical informatics was an emerging discipline. They stated that:
In the years between the emergence of the electronic digital computer and today, medical informatics was defined several times to reflect the directions and scientific advances in the field. Today, biomedical informatics can be defined as the theory and practice of information and knowledge integration, management, and use in all aspects of health care delivery, biomedicine, and public health, conducted through multidisciplinary research, development, and application. As such, biomedical informatics explores the adoption, development, and application of theory, methods and tools originating from a number of informatics-related disciplines in health care and the health sciences to support and eventually optimize the processes of:
Medical informatics is a non-exclusionary term that subsumes all health-related informatics sub-disciplines (e.g., Nursing and Dental Informatics). Furthermore, the term "Biomedical Informatics" is rapidly replacing "Medical Informatics" in the U.S. today (to reflect the increasing importance of the bioinformatics components of medical informatics efforts) whereas the most prominent term outside the U.S is still "Health Informatics". We use the term "Biomedical Informatics".
Milestones in the History of Biomedical Informatics
1940-1950: Von Neuman and Morgerstern develop the axiomatic foundations of formal Decision Making Theory.
1950-1970: Ledley and Lusted describe in their Science seminal paper ways by which computers can be used for medical diagnosis and therapy. Collen and colleagues investigate use of computers to improve clinical practice and outcomes at Kaiser Permanente. Warner and colleagues develop the first successful computerized diagnosis application (in the domain of congenital heart disease). Gorry, Barnett, and others develop systems based on Bayes theorem and extend the paradigm to include sequential diagnosis. Gorry outlines properties required for successful computer-based approache to diagnosis that many subsequent systems have adopted. Lindberg (CONSIDER) and Engle (HEME) develop criteria-based diagnostic systems. Bleich uses braching logic ("20 questions") to provide evidence-based support for diagnosis of acid-base disorders. The MUMPS programming language and operating system is developed as a time-sharing system that supports efficient storage and retrieval of text-based clinical records. The first "Reminder and Alerting" systems appear and their positive clinical impact is documented. Dedicated "legacy" systems, such as laboratory information systems (Lindberg) and pharmacy information systems begin to appear, along with commercial applications for admission/discharge/transfer, billing, and inventory. NLM introduces MEDLINE, a comprehensive computerized research literature database. Technicon develops the first Hospital Information System (HIS) at El Camino hospital in California.
1970-1980: Large-scale clinical information systems, such as hospital information systems (e.g., HELP at LDS Hospital in Utah) and electronic medical record systems (e.g., PROMIS at the University of Vermont) begin to appear at pioneering academic institutions, followed later by commercial products with limited capabilities. Several prototypic demonstration systems employ symbolic artificial intelligence methods to support diagnostic and therapeutic decision support. DENDRAL at Stanford is used to help deduce biochemical structures from mass spectrometry data. The INTERNIST-I system at the University of Pittsburgh covers the whole spectrum of internal medicine and is subsequently shown to perform diagnoses in very difficult cases with an accuracy equal to or at times better than that of experienced physicians. The MYCIN system for diagnosis and therapy of bacteremia and meningitis is developed and evaluated at Stanford. Kahneman, Slovic and Tversky explore and demonstrate the pitfalls of human judgment in diagnosis and other decision problems in their seminal book Judgement Under Uncertainty: Heuristics and Biases.
1980-1994: Foundation and growth of the American Medical Informatics Association to a professional membership organization of 3000-4000 members, subsuming the American College of Medical Informatics. Further development at leading academic sites of exemplary clinical information and electronic medical record systems (many sponsored through the National Library of Medicine's IAIMS initiative), with appearance of hundreds of new health-related informatics commercial endeavors. Wide-spread application of formal Decision-Making Theory to analyze and optimally solve prototypical medical problems. Emergence of medical informatics as an autonomous, rigorous field with well-defined focus and development of high-quality formal medical informatics research and training programs with long-term funding by NLM (U.S.). Adoption of medical informatics training, research, and development as high-priority strategic goals in both the U.S. and the European Union. Emergence of the Bayesian Network as the predominant model for decision-theory-compliant medical knowledge representation and reasoning. Exploration of sophisticated indexing and retrieval terminologies and systems. Wide-spread use of machine learning, data mining, and automated discovery methods in biomedicine. Development of messaging standards through Healthlevel 7 (HL7).
1995-Today: Development of extensive network-based applications, such as client-server clinical information systems. Widespread adoption of microcomputer-based clinical applications by medium-to-large sized hospitals and clinics (e.g., laboratory data display; display of textual documents). Explosive growth of Internet and World-Wide-Web-based applications (including telemedicine, telematics, and distributed databases). Near-completion of the Human Genome Project, with related explosive growth of bioinformatics research (including studies of the structure and function of micro and macro-biomolecules, linkage between genes and diseases, and comparative genomics), and commercialization of bioinformatics (by Celera and several other companies). Rise of consumer health informatics.
Biomedical Informatics Core Component Disciplines
Biomedical Informatics employs (and further adapts and develops) methods derived from a multitude of fields including: Information Science, Computer Science, Library Science, Cognitive Science, Business Management and Organization, Statistics and Biometrics, Mathematics, Artificial Intelligence, Operations Research, Economics, and of course, the (Basic and Clinical) Health Sciences.
Biomedical Informatics: Clinical or Basic Science?
Because biomedical informatics spans the spectrum from the theoretical to the applied, it has equally-developed "basic science" and "clinical" components. In addition, there is a strong component comprised of organizational theory and applications tailored to health-care systems and institutions.
Biomedical informatics expands beyond the narrow focus of biomedical computer systems design, application, and evaluation, by providing theory and tools for approaching health-related processes and research from an analytical and rational perspective. This is exemplified by its foundations in studies involving clinical problem-solving, research on improving diagnosis and therapy, the analysis of clinicians' information needs, and its emphasis on solutions that embody the evidence-based practice framework.
Selected Biomedical Informatics Resources
5. Commercial Software
6. WWW Resources