Strengthening perinatal healthcare utilization and quality of care for Indigenous and low socioeconomic status women through systems change: integrating person, provider, and policy perspectives.

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PROJECT SUMMARY The goal of this project is to identify high-efficacy and actionable strategies to improve perinatal healthcare utilization and perinatal healthcare quality (perinatal care utilization and quality; PCUQ) and reduce maternal morbidity (MM) rates and disparities experienced by for American Indian (AI) and low socioeconomic status women within a Northern Plains area. High rates of MM and disproportionate burden of MM experienced by marginalized groups has resulted in a wide range of recommendations to improve maternal health. Many recommendations focus on reducing barriers and enhancing facilitators (B/F) that will increase utilization of perinatal care or will improve the quality of perinatal care provided. However, there is little understanding of which B/F have the strongest impact on PCUQ and are therefore the most effective targets to improve PCUQ across the spectrum of person/patient, provider/health system and policy levels. This understanding is critical for actions that will reduce MM, as the association between PCUQ and MM is still unclear. Recommendations also rarely account the unique contexts of both cultural strengths as facilitators and systemic/structural racism as barriers experienced by AI communities, or contexts that impact the feasibility and success of implementing specific changes. To address these issues, this project involves building a community-based system dynamics simulation model that will detail the PCUQ B/F on person/patient, provider/health system and policy levels driving low PCUQ rates and disparities for AI and low socioeconomic status women (Aim 1). Models will be developed using a community-based participatory approach in collaboration with stakeholders who have personal and professional experience in the multiple components of PCUQ. This model will be simulated, and community-informed hypotheses will be tested to identify which B/F should be targeted as the best strategies for improving PCUQ and reducing disparity. Simulation models will be created in part with survey data from 380 women (65% AI) who live within the target communities and have had recent pregnancy and/or childbirth experience. This data will also be used to estimate path models that will evaluate PCUQ B/F as indirect effects on MM (Aim 2). Finally, we will develop qualitative community- based system dynamics models detailing the process of mechanisms that drive decision making and implementing actions for changes to perinatal healthcare practice and policy and the role of research during these processes (Aim 3). Models will be developed in collaboration with a sample of health system and policy decisionmakers and stakeholders, and with a sample of grassroots advocates for AI health and health equity to further evaluate equity or inequity within decision making and change processes. Key mechanisms for change and equity will be identified through network-based analysis of the qualitative model. The three studies detailed within this project will cumulatively critical information to improve maternal health and health equity for AI and low socioeconomic status women in a high need region, as well as a clear pathway for how this information should be utilized to implement the action plan that will be developed using project findings in collaboration with community stakeholders and collaborators.