Building a causal pathway framework to identify interventions to prevent severe maternal morbidity

The US is in the midst of a maternal health crisis. The US has worse maternal mortality (MM) than any other high-income country and is the only one for which the rate is increasing. Severe maternal morbidity (SMM), which encompasses conditions that put pregnant women most at risk of dying, doubled in the last two decades. This proposal focuses on SMM, as a sentinel outcome leading to MM, yet 100 times more common.

Most prior research on SMM has focused on proximal clinical factors (primarily related to co-morbidities and obstetric management); these factors alone are insufficient for understanding SMM. The objectives of this proposal are: 1) develop a causal pathway framework to understand how social determinants and more proximal health-related factors together contribute to SMM risk, and 2) use this framework to identify actionable strategies to reverse current trends. We will create a unique dataset that harmonizes 4 years of data from 6 states on 4.4 million births and 66,000 women with SMM. These states collectively include 1 in 4 US births and sufficiently varied social environments to disentangle complex multi-level drivers of maternal health.

Our focus is on social determinants from two specific domains: community resources and health care access, characterized at the county, neighborhood (census tract), and individual level. Health-related intermediaries include birth hospital quality of care, mode of birth, and maternal morbidities (eg, hypertension, anemia). These domains and intermediaries were selected for their known relevance to maternal health. In addition, we will evaluate impacts of 3 Quality Improvement (QI) collaboratives on SMM, which were designed to improve specific aspects of hospital quality of care and implemented by state-wide perinatal quality collaboratives (PQCs).

Our Specific Aims are: 1) Assess the relative and joint contributions of multi-level social determinants to SMM; 2) Identify potential health-related mechanisms by which multi-level social determinants affect SMM risk by conducting causal pathway analyses; and 3) Evaluate the impact of 3 QI collaboratives designed to reduce SMM (3a), and apply what we learn from the causal framework developed in Aims 1 and 2 to these state-specific contexts, to identify state-specific strategies for preventing SMM (3b). We currently have very limited understanding of how social determinants contribute to SMM. The proposed research will fill this important knowledge gap, which is an essential part of realizing sustainable improvement of maternal health.

Grant Number: 5R01NR020335-05
NIH Institute/Center: NIH
Principal Investigator: SUZAN CARMICHAEL