Christiana Care Health System’s Health Ambassador Program is a concerted, community health intervention to improve maternal and child morbidity and mortality. The Delaware Division of Public Health identified high-risk zip codes in the Wilmington, Delaware, metro area which had the lowest maternal and child health indicators in the state. Based on this, Christiana Care developed this community-based intervention to promote health before, during and after pregnancy. The objective is to connect pregnant women and families to health care, social services and education.  The program’s team consists of 5 community health workers, who conduct outreach within targeted zip codes. Their goal is to be integral in population health improvement, through a strong presence in the community and by building sustainable relationships with it. These Health Ambassadors directly refer community members to home visiting services. This is done by connecting with them one-on-one;  by sending the referral to the home visiting agency; and following up with both that agency and the community member to ensure the process has been completed. The Health Ambassadors have partnered with other community health programs within Christiana Care’s Department of Family and Community Medicine to bridge the gap between the health care system and community resources. We will present a process for developing a program using health ambassadors for communities at risk for low maternal and child health indicators. Preliminary data shows Health Ambassadors’ grassroots outreach, direct connection and presence in the community increased access to health care, social services and education for pregnant women and families.

Aim. To assess the development of and processes undertaken by the Florida Perinatal Quality Collaborative (FPQC) Quality Improvement (QI) Perinatal Indicator Pilot, framed within the plan-do-study-act (PDSA) cyclical model.

Methods. The Pilot involved seven Florida hospitals, eight state organizations, and five staff members, via bimonthly webinars, emails and phone calls. The perinatal data source was the 2004-2011 Florida linked database of maternal-infant hospital discharge records and birth certificates. Continued assessments of iterative PDSA cycles were conducted during the Pilot.

Results. Using the PDSA model, six webinars were held to identify five initial perinatal QI indicators, prioritize potential indicators, and develop a data quality report template. The Plan phase generated a practitioner-focused prioritized QI indicators list supported by both research and applicability. In the Do phase, staff generated and adapted the QI measures and produced a report draft. During the Study phase, FPQC stakeholders studied the indicators, provided feedback, and addressed concerns and potential pitfalls. Formal assessment was very good (4.6 of 5.0) for the measure description and adequate for the Q&A (4.2) and graphic formats (4.0) in the reports. This phase allowed incorporation of specific ideas, including an online version of the reports, data quality assessment, and critical risk adjustments for selected indicators. Last, the Act part of the cycle incorporated the stakeholders’ suggestions and looped back to a new PDSA cycle.

Conclusions. Following the PDSA model, the FPQC QI Pilot Indicator Project demonstrated feasibility, good standing with Florida stakeholders, and potential improvement opportunities with Pilot and future full-scale activities.

Background: Infant Mortality Rate (IMR) is a vital indicator of community health status; as it is correlated with maternal health access, public health practices, socio-economic conditions, and environmental factors. The United States ranks 26^th in the world, and Ohio ranks 47^th in the nation for IMR. Healthy People 2020 objectives include decrease of IMR to 6%.  Method: Data from the CDC, the Ohio Department of Health Office of Vital Statistics, ESRI and the U.S. Census Bureau were used. The data ranged from 2007-2012 and documented the number of infant mortalities by county in Ohio. The analysis was done using, Geographical Information System (GIS) on ESRI’s ArcGIS. The research objectives of this study were to determine how race and socio-demographic factors such as income and education influences IMR. In addition, the study looked at county level data to investigate diversity in the relationship of socio-demographic factors and IMR.  Results:  This study results showed that race/ethnicity and socio-demographic factors such as income and education have a significant impact on IMR, which varied by counties in Ohio. Conclusion: Implications of this study highlight the needs of policies to focus specifically on regional diversity and socio-demographic factors to reduce IMR and meet the Healthy People 2020 objectives.

In comparison to other wealthy countries, the United States ranks near the bottom for infant mortality.  Ohio’s black infant mortality rates are the second worst in the country.  In 2012, Franklin county black infants died at more than twice the rate of white infants, 12.9 and 6.0, respectively. Assessing a community’s readiness to address the issues of infant mortality is a critical factor in implementing effective interventions to address health disparities but has not been assessed within Ohio’s urban area.  The Community Readiness Model (CRM), a theoretical basis for understanding and increasing community readiness, was implemented to measure community attitudes, perceptions, and knowledge regarding black infant mortality within Columbus.

     Semi-structured key informant interviews with community leaders from in five “hot spot” areas with the highest black infant mortality rates in Franklin County.  The interview primarily consisted of open-ended questions within the following five dimensions: community knowledge of the issue, community knowledge of efforts, community climate, leadership, and resources. The interviews were transcribed, and a mixed-method approach was employed using a quantitative scoring process of the CRM and a thematic analysis of key words. 

     Findings of the Community Readiness assessment validated our study hypothesis about the lack of robust awareness about the issues of black infant mortality amongst community members and leadership.  Results from the study helped guide stage-appropriate strategies provided in the CRM. Recommendations to engage the community included unconventional partnerships, target media campaigns, faith community involvement, planned interventions addressing the social determinants of health and engagement of community leaders.

Background: Mothers receive infant care education prior to hospital discharge and from their pediatricians. However, this may be insufficient to adequately educate parents about the importance of a safe sleep environment. A safe sleep environment includes: always placing infant on the back to sleep, having a separate infant sleep place removing all objects from sleep space, and avoiding infant’s exposure to smoking.

Methods: Research personnel administered in-person surveys to mothers 18 years or older, with infants aged 2 weeks to 3, months during their UNTHSC-Pediatric Outpatient Clinic visits.

Results: Of 103 mothers, 46 (44.7%) mothers surveyed were Hispanic, 28 (27.2%) were White/Caucasian, and 18 (17.5%) were Black/African-American. Our survey showed that 73 (70.9%) infants started sleeping in a crib in mother’s room; however, 38 (36.9%) slept in mother’s bed at some point during the night and 26 (25.2%) infants usually awoke in mother’s bed. Twenty five mothers (24.3%) put their baby to sleep on a side or prone position. African-American mothers were 2.87 times more likely to put their baby to sleep on either side or prone position than non-African American mothers. Few of infants, 11 (10.7%) slept with a pillow or bumpers. Most of mothers, 86 (83.5%) reported that no one is allowed to smoke inside their home.

Conclusions: Understanding parents’ infant sleep environment practices can contribute to the creation of targeted patient education. Healthcare professionals should address with parents the risk of bed-sharing, prone and side sleep positions, inconsistent sleep environment and having objects in infant sleep space.