, Volume 16, Issue 2 Supplement, pp 196-202

Building Analytic Capacity, Facilitating Partnerships, and Promoting Data Use in State Health Agencies: A Distance-Based Workforce Development Initiative Applied to Maternal and Child Health Epidemiology

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Abstract

The purpose of this article is to summarize the methodology, partnerships, and products developed as a result of a distance-based workforce development initiative to improve analytic capacity among maternal and child health (MCH) epidemiologists in state health agencies. This effort was initiated by the Centers for Disease Control’s MCH Epidemiology Program and faculty at the University of Illinois at Chicago to encourage and support the use of surveillance data by MCH epidemiologists and program staff in state agencies. Beginning in 2005, distance-based training in advanced analytic skills was provided to MCH epidemiologists. To support participants, this model of workforce development included: lectures about the practical application of innovative epidemiologic methods, development of multidisciplinary teams within and across agencies, and systematic, tailored technical assistance The goal of this initiative evolved to emphasize the direct application of advanced methods to the development of state data products using complex sample surveys, resulting in the articles published in this supplement to MCHJ. Innovative methods were applied by participating MCH epidemiologists, including regional analyses across geographies and datasets, multilevel analyses of state policies, and new indicator development. Support was provided for developing cross-state and regional partnerships and for developing and publishing the results of analytic projects. This collaboration was successful in building analytic capacity, facilitating partnerships and promoting surveillance data use to address state MCH priorities, and may have broader application beyond MCH epidemiology. In an era of decreasing resources, such partnership efforts between state and federal agencies and academia are essential for promoting effective data use.

Disclaimer The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.