|Perinatal Disparities Diagram|
Racial and ethnic disparities in rates of pregnancy-related death have persisted for more than 30 years. Inequities in perinatal health care are unacceptable, and quality and safety initiatives are needed to ensure equitable care for all women and newborns. A quality improvement (QI) approach has been successfully used to improve clinical outcomes, suggesting that QI can be a powerful tool to eliminating disparities.
The Institute for Perinatal Quality Improvement used the Ishikawa diagram format and the Socio-Ecological Model to develop the Socio-Ecological Perinatal Disparities Ishikawa Diagram. Published in 2019 paper by Debra Bingham, DrPH, RN, David K. Jones, PhD and Elizabeth A. Howell, MD, MPP, this tool is recommended to help determine root cause and can be used along with additional quality and safety strategies to guide national, state, and hospital-based efforts to eliminate disparities in perinatal outcomes and to ensure equity for all women and newborns.
What is the Socio-Ecological Model?
This framework is commonly used by public health leaders to guide systems approaches to analyzing and identifying solutions to complex problems. The key insight of the Socio-Ecological Model is that a person’s health is not just a function of his or her individual behaviors present in factors present in the societal context, community, and relationships.
What is an Ishikawa diagram?
Also known as cause-and-effect or fish bone diagrams, these diagrams are used by quality and safety leaders to understand the key components in a system that led to a failure or contributed to a poor outcome.
Socio-Ecological Perinatal Disparities Ishikawa Diagram
How to Use This Tool
The diagram identifies factors that contribute to perinatal disparities and each factor can be eliminated using quality improvement methods. The five QI strategies outlined in the paper are:
1) Apply a systems approach based on the sociological model
2) Identify root causes of disparities
3) Identify and eliminate strong but wrong routines
4) Use improvement and implementation science tools
5) Use data to guide the plain and track progress