Laël Gatewood, Health Informatics - the University of Minnesota

Dr. Lael Gatewood Professor Laël C. Gatewood, Ph.D., F.A.C.M.I
Laboratory Medicine and Pathology
Medical School
Epidemiology and Community Health
School of Public Health
University of Minnesota

Dr. Gatewood is Co-Director of a major National Library of Medicine (NLM) training grant in medical informatics, one of the first programs in the field now in its 30th year of NIH funding. This program provides informatics research opportunities, graduate programs, practice settings and computer resources for medical and graduate students, health professionals and postdoctoral fellows. She is also Director of the Neuroinformatics Core for the International Neuroimaging Consortium (INC). She supervises outreach activities for the collaborator, including the Website, interactive demonstrations, tutorial presentations and conference coordination.  She has been active in clinical research and its information systems support for the past 30 years. Other research interests include regional immunization registries, integration of public health recording systems, health information exchange and other applications of public health informatics. A current area of research is the development of health information sharing systems for interprofessional teams working in transitional care.

Dr. Gatewood was previously Director of the National Micropopulation Simulation Resource (NMSR), funded by NIH (National Center for Research Resources) 1983-1998 to promote the use of Monte Carlo and micropopulation models in biomedical research. The NMSR center was unique in that it explored micropopulations of interest to epidemiologists, demographers and those in health services research. In micropopulation simulations, each subject can have a different time course for discrete events, which allows analysis of natural disease patterns, prevention and/or interventions over a period of time. It was also possible to assemble a population with known genetic characteristics against which to test new methods of genetic analysis, as in linkage or segregation studies. The models were used to simulate population patterns of infectious disease as well as to study chronic diseases such as heart attack, stroke, cancer, arthritis, and diabetes. These studies helped scientists understand how disease traits spread through generations, new methods of primary/secondary prevention and the role of risk-factor exposures, such as smoking or diet. Other studies included the complex pattern of intravenous drug use and HIV infection, as well as the efficacy of treatments in a simulated closed population in high-risk areas. Similar models helped to evaluate patterns of influenza infection and vaccine efficacy in confined populations such as nursing home residents and children in day-care centers.

Research Interests:

Micropopulation Simulation
Clinical Research Information Systems
Child Health Records
Health Information Exchange
Nursing Informatics
Public Health Informatics

Selected References:


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Last modified on Monday Dec 12, 2005

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