The Maternal Mortality and Morbidity Interactive Dashboard (3MID)

The Maternal Mortality and Morbidity Interactive Dashboard (3MID) analyzes how budgeting, social determinants of health, medical interventions, and policy can reduce rates of maternal morbidity and mortality across the United States. It incorporates local factors, including state-specific demographics and resources, to enhance outcomes for priority populations that include rural residents, racial and ethnic groups, and groups that have been economically marginalized.


Overview of Maternal Health

The United States is the only developed nation in the world with an increasing maternal mortality rate. Nearly 1,000 women die each year from pregnancy or pregnancy-related complications. Approximately 50,000 women suffer from severe complications of pregnancy (e.g., severe maternal morbidity). Non-Hispanic Black and American Indian/Alaska Native women are 2-3 times more likely to suffer a pregnancy-related death than Non-Hispanic White women. Many rural counties have also lost their hospital-based obstetric services, creating “obstetric deserts” where women must travel long distances to access care. These challenges have led to the development of the Maternal Mortality and Morbidity Interactive Dashboard (3MID), which creates a virtual environment for researchers to test interventions designed to reduce maternal morbidity and mortality rates, especially for marginalized communities.

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Data Challenges

Current data rates are potentially undercounting pregnancy-related deaths due to discrepancies in definitions and inconsistencies in data collection, analysis, and reporting. The following recommendations can shape national data discussions: 1) create a common language to classify and review maternal mortality rates. 2) ensure the pregnancy checkbox on death certificates is applied correctly, 3) provide guidelines for Maternal Mortality Review Committees, 4) develop data collection policies on race, ethnicity, insurance coverage, hospital or licensed birthing center information, comorbidities, and co-occurring diagnoses, 5) conduct and share comprehensive maternal mortality and morbidity assessments on understudied population groups, and 6) require and support states to share maternal mortality data with the Centers for Disease Control and Prevention (CDC).

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3MID Dashboard Overview

3MID pulls data from a synthetic population of pregnant women (to protect privacy simplify data handling) and assesses the risk of maternal mortality at the individual level based on demographic and morbidity data. Data sources: Institute for Health Metrics and Evaluation (IHME)’s Synthetic Populations and Ecosystems of the World (SPEW), March of Dimes PeriStats & maternal care deserts data, Center for Medicare and Medicaid Services (CMS). The user can select the geographic region, hospitals in a system, the quality improvement toolkit to deploy, and the simulation time period (e.g., 1-, 3-, 5- years). All deaths in the simulation are assigned a probability-based cause of death that corresponds to the leading causes of maternal death in that state. Each of the specific cause toolkits have a “chance of prevention” metric that is triggered if the toolkit is deployed. The number of total deaths and prevented deaths are then shown as outputs.

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Case Study to Prevent Maternal Death in Alabama

Dashboard View: Marion County, AL has a calculate rate of maternal disorders and was deemed a maternal care desert. Hospital View: Every hospital within Alabama is currently being displayed. The user can select a particular hospital to view the capacity of the hospital, the rurality of the hospital, and the overall rating of the hospital. We included an overall rating via CMS Hospital Compare. Individual Level Demographic View: Each dot represents a Non-Hispanic Black, Non-Hispanic White, Hispanic, or other women. A user can see the age, race, income, and employment status of the women. These factors, the rates of maternal disorders, and if the woman lives in a maternal care desert determines the maternal risk score of the woman.

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