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The Impact of Medicaid Managed Care on Obstetrical Care and Birth Outcomes: A Case Study
1Department of Economics, Appalachian State University, Boone, North Carolina.
As Medicaid has increasingly financed managed care plans since the 1990s, it is important to understand the corresponding impacts on the well-being of disadvantaged mothers and infants. This study examines how a Medicaid managed care (MMC) program in Pennsylvania (PA) impacts disadvantaged women's obstetrical care utilization and access as well as their birth outcomes. This study uses a dataset of PA disadvantaged women who had multiple singleton births in 1994-2004. As to the empirical approach, we apply a linear multiple regression model to implement a pre-post design with control groups. The model also controls for unmeasured maternal birth-invariant characteristics, which affect take-up of Medicaid coverage and managed care plans. The sample for the main analysis consists of 78,346 sibling births. We find the program roll-out reduces usage of some high-tech obstetrical services and limits access to high-quality hospital services, thereby contributing to cost savings. However, implementation of the program is also associated with deterioration in birth outcomes, worse prenatal care, and an elevated risk of inappropriate gestational weight gain. Cost containment through transition to MMC can be fulfilled at the price of maternal health care utilization and infant welfare. Therefore, caution is needed in design and delivery of managed care to low-income women.
As Medicaid has increasingly financed managed care plans since the 1990s, it is important to understand the corresponding impacts on the well-being of disadvantaged mothers and infants. This study examines how a Medicaid managed care (MMC) program in Pennsylvania (PA) impacts disadvantaged women's obstetrical care utilization and access as well as their birth outcomes. This study uses a dataset of PA disadvantaged women who had multiple singleton births in 1994-2004. As to the empirical approach, we apply a linear multiple regression model to implement a pre-post design with control groups. The model also controls for unmeasured maternal birth-invariant characteristics, which affect take-up of Medicaid coverage and managed care plans. The sample for the main analysis consists of 78,346 sibling births. We find the program roll-out reduces usage of some high-tech obstetrical services and limits access to high-quality hospital services, thereby contributing to cost savings. However, implementation of the program is also associated with deterioration in birth outcomes, worse prenatal care, and an elevated risk of inappropriate gestational weight gain. Cost containment through transition to MMC can be fulfilled at the price of maternal health care utilization and infant welfare. Therefore, caution is needed in design and delivery of managed care to low-income women.
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