Investigating Ohio’s High Infant Mortality

Ohio continues to struggle with high levels of, and significant disparities in, infant and maternal mortality, unintended pregnancies, and health care coverage and access, including access to contraceptive and abortion services. Our research aims to answer the following question:

How do social determinants of health, biases, attitudes, cultural norms, laws, and policies in urban Ohio impact access to and use of reproductive and other health services (e.g. contraception, abortion, prenatal care, birth care), pregnancy, and maternal and child health?”

Our project began by gathering groups of stakeholders from community and advocacy organizations, local and state public health, and health care administrators to generate collective knowledge about the processes driving high infant and maternal mortality and the complex relationships between multiple determinants operating at multiple levels (e.g., individual, community, organizations, and policies). We then applied system dynamics modeling to produce mathematical descriptions of these processes and to provide decision-makers with tools to conduct “What if?” analysis for multiple reproductive health outcomes and policy interventions.

Our project created the following tools, which stakeholders interested in transformative solutions to the question above can utilize for planning purposes and to gain additional insights into the complexity of the reproductive health system. To learn more about these tools, please view our short explainer video below.

Causal Loop Diagram

The first tool is a causal loop diagram, which is a type of concept map, that was created by a group of diverse stakeholders during five sessions as part of a group model building workshop. To learn more about the group model building workshop and community-based system dynamics approach, please view our research methodology overview.

Policy Dashboard

The second tool is a policy dashboard that was created based on the causal loop diagram. The purpose of the policy dashboard is to allow decision-makers in charge of setting and implementing policies in the reproductive health system to identify policies that optimally reduce the gap in infant mortality rate between Black infants and white infants. The dashboard is interactive and allows the user to run a “What if?” analysis by changing the level of investments in certain types of policies that may close the gap in infant mortality rate even faster than if we made no additional investments. The data used to inform this dashboard is from Franklin County, Ohio.

The causal loop diagram and policy dashboard are not accessible to screen readers. For assistance or if you have any questions, please contact the lead investigator, Dr. Ayaz Hyder.

Findings

Team Members