title: Longitudinal research databases in medical education: facilitating the study of educational outcomes over time and across institutions.
abstract: Many education research questions cannot be answered using participants from one institution or short periods of follow-up. In response to societal demands for accountability and evidence of effectiveness, new models of research must be developed to study the outcomes of educational activities. Following the 2007 Millennium Conference on Medical Education Research, organizers assigned a task force to explore the use of longitudinal databases in education research. This article summarizes the task force's findings. Similar to the Framingham studies in clinical medicine, longitudinal databases assemble prospectively collected information to retrospectively answer questions of interest. Many studies using such databases have been published. The task force identified three general approaches to database-type research. First, institutions can obtain identified information from existing sources, link it with school-specific information and other identified information, deidentify it, and merge it with similar information from other collaborating schools. Second, researchers can obtain from existing sources deidentified information on large samples and explore associations within this dataset. Third, investigators can design and implement databases to prospectively collect trainee information over time and across multiple institutions for the purpose of education research. Although costly, such comprehensive, purpose-built databases would ensure the availability of information needed to answer a variety of medical education research questions. Millennium Conference participants believed that stakeholders should explore the funding and development of such prospective databases. In the meantime, education researchers should use existing sources of individualized learner data to better understand how to develop competent, compassionate clinicians.
authors.affiliation: Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA. cook.david33@mayo.edu
authors.forename: David A
authors.initials: DA
authors.lastname: Cook
authors.forename: Dorothy A
authors.initials: DA
authors.lastname: Andriole
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Durning
authors.forename: Nicole K
authors.initials: NK
authors.lastname: Roberts
authors.forename: Marc M
authors.initials: MM
authors.lastname: Triola
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D015510:Clinical Medicine / Q000193:education*; D019992:Databases as Topic; D004501:Education, Medical / Q000706:statistics & numerical data*; D004521:Educational Measurement / Q000379:methods*; D005500:Follow-Up Studies; D006801:Humans; D015233:Models, Statistical; D011446:Prospective Studies; D012577:Schools, Medical; D013997:Time Factors; D014481:United States