Sunday, 28 July 2019: 8:00 AM
Developing a base of evidence on the efficacy of mobile health has been a goal since inception for the Text4baby program. Text4baby’s power lies in its ability to get the most essential health information to mothers in need quickly and easily using a technology they regularly use and rely on. Over 95% of Americans own a cell phone and 81% of cell users send or receive text messages regularly. Text4baby is a data-driven initiative and provides its partner network with text4baby data by zip code and in real-time so program and strategies can be targeted accordingly. The goals of the text4baby evaluation acknowledge the importance of assessing the efficacy of mobile health interventions, both as they apply to maternal and child health and how such technology can be used to address other health issues facing underserved populations. Much can be learned about the implementation of text4baby from multiple perspectives: real-time data, partners, providers, and users. Moreover, the data can shed light on trends at the national level in designing and implementing the program as well as how communities engage in the text4baby program in a local context. Understanding the data will add significantly to the evidence base that will bolster the development of mHealth and related initiatives in other public health interventions, such as healthy behavior applications focused on weight management, nutrition, and smoking cessation and disease management applications. The findings from the demographic data may also inform efforts to target hard-to-reach populations in international venues. The conceptual framework and logic model guiding the Text4baby program evaluation will be described. Breakthroughs in data-capturing technologies, data standards, data storage and modeling have created opportunities for community and health care industry partners to use data and analytics of large, at scale mHealth programs to analyze demographics. Following the analysis of demographic data, community and healthcare industry partners are informed and have the ability to identify data-driven strategies and target areas. Case presentations showing how Text4baby data informed community program strategies will be discussed. One example of a local case presentation is the B’more for Healthy Babies program. Baltimore City Health Department promoted Text4Baby as an educational health promotion strategy, and strategically targeted neighborhoods through the use of community/peer educators. These peer educators were recruited through a collaboration between the Mayor’s Office of Employment and Development (MOED) YouthWorks program and B’more for Healthy Babies. Peer/community educators canvassed three targeted neighborhoods. B’more for Healthy Babies team evaluated the community outreach project. This was accomplished through a focus group and descriptive survey that was focused specifically on the Text4Baby outreach. In addition, the team used the Text4baby partner data to help understand the demographics and program enrolment trends.. An example of a regional and national case presentation will also demonstrate how the use of real-time program data informed community and health care program strategies and guided investment of resources. Next steps will be identified as to how large government health care programs and plans can use real-time data analytics to understand the demographics of who they are serving. National, regional, and local partners analyzing the real-time data and trending the demographics of program users will contribute immensely to the evidence base on the efficacy of mobile health.