Childbirth should be a safe and joyous occasion as parents welcome a new member into their family. Still, too often, that joy is overshadowed by maternal complications, including maternal and infant death.

Each year in the United States, as many as 60,000 women experience severe, unexpected health problems related to pregnancy that affect the long-term health of the mother and infant.

According to the Centers for Disease Control (CDC), about 700 women die each year in the US as a result of pregnancy or delivery complications. The CDC also estimates that 60 percent of these deaths could have been prevented.

Applying a health equity lens

Infants account for 3.4% of the US population, approximately 11.4 million. In 2020, nearly 20,000 infants died in the US. The infant mortality rate (IMR) for the US is 5.5 deaths per 1000 live birth. There was a slight decrease in the number of deaths in 2022 by one percent from the previous year. Numerous factors contribute to infant mortality, including preterm delivery, low birth weight and maternal complications. Two-thirds of infant deaths occur within one month after birth.

Furthermore, maternal outcomes significantly correlate with access to early prenatal and post-delivery care. We cannot overlook the need to address healthcare disparities that many pregnant women face that result in maternal and infant complications. Assessing maternal outcomes across different populations quantitatively correlates mortality rates by race, age and socioeconomic factors.

In the US, there is an overwhelming disparity in maternal deaths for black and brown women, who experience 3.2 times higher than average death rates than white women. In addition, preterm and low birth weight deliveries are the unintended outcome of pregnancy complications and the leading cause of infant mortality. Infants born to women of color are twice as likely to die relative to white women.

Pregnant women face many other challenges affecting maternal and infant outcomes during the pregnancy lifecycle including:

  • Gaps in care: Women of color are often uninsured and overrepresented in Medicaid maternal care population and that coverage ends 60 days after delivery.
  • Rural health services: According to the American Hospital Association, 50% of rural hospitals no longer offer obstetric care services.
  • Chronic health conditions: Women of color often have medical conditions related to socioeconomic factors, such as diabetes and hypertension, placing them at a higher risk of complications.
  • Transportation, housing and food insecurities.
  • Structural racism: Policies that perpetuate discrimination, such as redlining. Redlining reduces access to needed services and care, such as supermarkets and pharmacies within communities, or a lack of broadband access that reduces the ability to perform telehealth visits or remote monitoring.

With the range of negative outcomes due to certain factors in maternal care, analytics and policy changes have an opportunity to mitigate risks and complications associated with pregnancy.

Making a difference with policy changes and analytics

Insurance payers must evaluate whether policy changes, such as expanding services and improving care access, improve outcomes. Recently, insurance payers, especially Medicaid, which covers over 45% of all births in the US, have made changes to improve maternal health, such as:

  • Extension of postpartum coverage from 60 to 90 days (adoption varies by state).
  • Reimbursement for doula services (not widely adopted by states).

Providers are also challenged with early identification of risk factors, inability to address socioeconomic barriers and integration of preventative measures. Pairing policy changes with analytics can help payers assess current policy outcomes and demonstrate the impact of future policies and services.

Using advanced analytics, predictive models can be created to detect and notify providers during the early stages of pregnancy of risk factors for maternal complications. Artificial intelligence (AI) and machine learning (ML) models can detect gaps in care, such as missed prenatal and postpartum visits and identify network adequacy. Once risks are identified, providers can facilitate early interventions such as home monitoring equipment to evaluate blood pressure, weight and blood sugar to identify pre-eclampsia and other risks.

Advanced analytics is designed to integrate data that allows providers to address other obstacles, such as:

  • Identifying prenatal and postpartum care gaps.
  • Identifying clinical and socioeconomic risk factors that contribute to pregnancy complications.
  • Providing real-time data sharing for targeted case management.
  • Unveiling variations in care pathways to improve equitable outcomes.
  • Mitigating the long-term health impact of pregnancy-related complications.
  • Providing insight into drivers of the financial cost of pregnancy-related complications.
  • Evaluating the effect of maternal health services and reimbursement models.
  • Recommending policies and services that increase access to care and improve outcomes.

Moving forward

Many contributing demographics and socioeconomic factors shape maternal outcomes. Healthy babies begin with healthy mothers. Every pregnant woman should have access to the prenatal and postpartum care needed to ensure a healthy baby. Advanced analytics and policy changes provide tools to drive better decisions that improve access to that care and impact maternal outcomes. Let’s work together to reduce disparities in maternal care and bring the joy of healthy childbirth to every family.

Want to learn more? See other ways SAS is making a difference in health care with analytics. 

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About Author

Lisa Lucas

National Director Healthcare Informatics

Lisa is currently the National Director of Healthcare Informatics at SAS. Lisa has supported healthcare informatics and analytics for many years both in acute care settings and private sectors. She is working closely to support federal and state initiatives at SAS by refining and implementing analytic services from a clinical perspective. She is a faculty member at the University of Mary Washington, teaching Healthcare Technology and Informatics. She has a Bachelor of Science degree from George Mason University, dual master’s degrees in Business Administration and Healthcare Management, and a Doctor of Nursing Practice from American Sentinel University in Colorado. She also holds certifications in Nursing informatics, Certified Professional in Health Information Management from HIMSS, and Certified Nurse Educator.

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