Teaching Internal Medicine Residents to Care for Reproductive-Age and Pregnant Women: An Effective Web-Based Curriculum

Abstract

Background: We sought to determine whether a Web-based curriculum could improve internal medicine residents' perceived preparedness and knowledge in the areas of preconception care, infertility evaluation, and management of medical conditions during pregnancy. Training in these areas has been previously identified as inadequate. Description: Three Web-based modules were developed to teach these topics. Seventy residents at one institution were invited to complete the modules and to participate in the curriculum's evaluation over 6 months. Evaluation: Paper questionnaires assessed preparedness and comfort level among all participants. Web-based surveys that assessed pre/postknowledge and satisfaction among module completers accompanied each module. Ninety-seven percent completed paper questionnaires, and 59% completed 1 or more modules. At the end of the study period, module completers felt significantly more prepared than noncompleters, and improvement in comfort level was strongly associated with the number of modules completed. Knowledge improved significantly with module completion and curricular satisfaction was high. Conclusions: A Web-based approach to teaching these topics to internal medicine residents increased knowledge and perceived preparedness and was well received.

During the period in which this research was conducted, Dr. Spagnoletti was supported by a Veteran's Administration Special Fellowship in Women's Health. The research was supported by a General Internal Medicine Development Award from the University of Pittsburgh.

We acknowledge the contributions of Gary Tabas, MD, Janine Frank, MD, and Doris Rubio, PhD, and we thank the staff members of the Center for Research on Health Care Data Center at the University of Pittsburgh for their assistance with data management and the staff of the University of Pittsburgh Laboratory for Educational Technology, particularly Peter Kant, for his instructional design expertise, and Jane Alexander, for her computer programming expertise.