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Fetal and Infant Mortality Review(FIMR): Using Qualitative Data to Address Issues Related to Health Disparities

Ellen Hutchins, ScD, MSW, Chief, Perinatal and Women's Health Branch, Maternal and Child Health Bureau, Parklawn Bldg Rm 10C-16, 5600 Fishers Lane, Rockville, MD 20857, 301.443.9534, ehutchins@hrsa.gov and Kathleen Buckley, MSN, CNM, Director, National Fetal and Infant Mortalty Review Program, 409 12th Street, SW, Washington, D.C., DC 20024.

The US infant mortality rate decreased to 6.9 in 2000, approaching the 2010 national goal of 4.5 infant deaths per 1,000 live births. However, this decrease is not uniform across many of the nation’s communities and racial/ethnic groups. Infants born into poor families are still twice as likely to die as those born to families above the poverty level. The African American community incurs the greatest disparity in infant mortality with the rate, at least, double that for white infants. Qualitative FIMR information complements local population-based fetal and infant mortality data. It identifies critical community strengths as well as unique health/social issues associated with disparities in outcomes. New research suggests the importance of the inclusion of such qualitative information to understand disparities among racial and ethnic groups. Specifically, that qualitative information includes: 1)community based review and decision-making; 2) input from community key informant interviews and 3) re-examination of stress and social support as they relate to preterm births. The FIMR program is a model that builds community decision-making capacity and identifies gaps in services and systems. FIMR sponsors key informant interviews of mothers who have experienced a loss and views that information as key to understanding community issues associated with health disparity. Finally, the NFIMR home interview survey has always included questions about stressors and social support. The qualitative FIMR methodology can offer a unique strategy for analyses of individual and community factors, which significantly affect health disparities and are not discoverable through analyses of population based data.

Learning Objectives:

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.

Topics in Maternal and Child Health

The 132nd Annual Meeting (November 6-10, 2004) of APHA