Premier’s own Maternal Health Trends Analysis, which examined data from the PHD and included standardized inpatient data from 10.9 million births that occurred in 921 hospitals across 547 states between 2008-2020, noted that the proportion of individuals giving birth over the age of 35 increased from 14 to 18 percent from 2008 to 2020, respectively.
The analysis also found that severe maternal mortality (SMM) had an increase of 17 percent and SMM among individuals aged 45 and over tended to be higher than in individuals in the 15 to 44 age range.
As the average maternal age ticks upward and maternal mortality rates continue to increase, each death highlights the need for relevant data sources that can illuminate risk factors that contribute to maternal and infant harm.
Research efforts should be aimed at understanding risk factors associated with clinical conditions and diseases that impact health outcomes as well as identifying social determinants of health (SDOH) and disparities that contribute to maternal and infant deaths.
Pregnant people are more cautious about what they put into their bodies, from food to medications, they need clear data and strong recommendations from solid research. We must include them in future clinical studies to make strong evidence-based recommendations, recognize risk factors and better prepare for the next pandemic, if or when it happens.
Enter the PINC AI Maternal Health Database
Life sciences companies and health systems are seeking to do this through insights gained from pregnant and lactating populations. Yet, this ability to analyze maternal health outcomes that link maternal data to newborn data has been difficult to accomplish on a large-scale population until now. The PAS team has created the PINC AI Maternal Health Database that links mothers to their infants and can illuminate the entire pregnancy journey from prenatal follow-up to birth to post-partum.
The PINC AI Maternal Health Database provides actual maternal age, links encounters of mothers and their babies and enables access to more than three years of retrospective data, as well as future prospective data options.
Here are three ways life sciences companies can utilize the PINC AI™ Maternal Health Database to inform clinical research and evidence-based outcome improvement strategies.
· Generate real-world evidence and population-based analyses. This dataset helps researchers and clinicians identify existing health risks for birthing people and those resulting from pregnancy to prevent negative health impacts on both pregnant people and their infants. Linking the inpatient data of mothers and their infants allows researchers the opportunity to identify if direct causes of maternal morbidity and mortality increase a newborn infant’s risk of lifelong morbidity and mortality. Researchers can use this comprehensive data to evaluate concomitant conditions, procedures, resource utilization, healthcare economics, clinical outcomes, and their impact on maternal and infant health to inform strategies to reduce maternal and infant harm.
· Study the patient journey from pregnancy to post-partum. The PINC AI™ Maternal Health Database provides researchers with longitudinal data that follows mothers and their infants in tandem and can illuminate the entire pregnancy journey from prenatal to post-partum and beyond. This linked data provides details such as actual maternal age, race, ethnicity, birth events and outcomes and can be linked with PINC AI ™ claims data to generate actionable information that may inform evidence-based clinical practice.
· Advance health equity and improve outcomes. This HIPAA-compliant, maternal-infant linked data helps researchers and clinicians understand and address health equity by identifying racial, ethnic and geographical disparities in care to help develop strategies to reduce risks for pregnant people and infants most susceptible to poor health outcomes.
Protecting Maternal and Infant Health through Research
It goes without saying that maternal and infant health are a national priority for the U.S. and recently, the Biden-Harris Administration shared their blueprint to improve the health and wellbeing of birthing people and infants in America. This administration is taking important steps to accomplish this goal, including the launch of the Maternal Morbidity and Mortality Data and Analysis Initiative with Premier and a commitment to a proposed maternity care quality hospital designation.
In addition, the Centers for Medicare and Medicaid Services (CMS) recently finalized their new Maternal Morbidity Structural Measure that is aimed at ensuring health systems use evidence-based best practices across the continuum of care.
These designations, initiatives and measures are just the beginning of our efforts. We must work to ensure that future research includes pregnant and lactating populations to better understand the effects that medical solutions, vaccines and evidence-based clinical practices can have on mothers and their infants. Our efforts must be aimed at reducing maternal morbidity and mortality, reducing harm, driving clinical quality improvements, advancing health equity, and reducing disparities for all people giving birth.
The PINC AI Maternal Health Database, a de-identified, HIPAA-compliant database, is one part of the complex solution to addressing maternal and infant health. Connect with us and learn how you can use this database to inform your research efforts, create evidence-based best practices and reduce the chances of maternal and infant harm.
This content was originally published here.