Research Brief
Using an Innovative Database and Machine Learning to Predict and Reduce Infant Mortality
Feb 4, 2021
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Poor birth and infant outcomes and pronounced racial disparities persist in Allegheny County, Pennsylvania, despite robust maternal and child health and social service systems. The authors use predictive models of which interventions women are likely to participate in, develop a causal inference framework to estimate the effectiveness of those interventions, and reveal how that effectiveness varies for women with different risk and other factors.
Chapter One
Introduction
Chapter Two
Methods
Chapter Three
Intervention Types and the Evidence Base
Chapter Four
National, State, and Local Infant Mortality Prevention Efforts
Chapter Five
Inventory of Allegheny County Programs, Services, and Supports Related to Preventing Infant Mortality
Chapter Six
Allegheny County Birth Outcomes, Risk and Contextual Factors, and Intervention Participation
Chapter Seven
Understanding Participation in Select Programs, Services, and Supports in Allegheny County
Chapter Eight
Examining Effectiveness of Select Programs, Services, and Supports in Allegheny County
Chapter Nine
Examining Variation in Effectiveness for Select Allegheny County Programs, Services, and Supports
Chapter Ten
Recommendations and Next Steps
This research was sponsored by the Richard King Mellon Foundation and conducted by the Social and Behavioral Policy Program within RAND Social and Economic Well-Being.
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