Scaling Evidence: National Causal Evaluation of Perinatal Quality Collaboratives Needs Better Data

Abstract Perinatal Quality Collaboratives (PQCs) have been widely adopted across U.S. states to improve maternal-infant health care delivery and outcomes, yet rigorous evidence of their national impact on maternal mortality and severe maternal morbidity remains limited. This commentary identifies two fundamental challenges constraining causal inference in PQC evaluations. First, inconsistent measurement of key outcomes, stemming from staggered state adoption of revised vital statistics certificates and coding changes, confounds attempts to distinguish genuine health improvements from data artifacts. Second, the causal pathway from state-level PQC adoption to health outcomes involves multiple intermediate changes in clinical practices and care delivery that remain unobserved in administrative data. This imprecision in treatment measurement, combined with rare outcomes, severely limits statistical power, especially for analysis of subpopulations at increased risk of adverse maternal-infant health outcomes (e.g., Black women, those in low-income communities). We recommend establishing a national registry to track quality improvement initiatives systematically, investing in harmonization of vital statistics data across states and time periods, and exploring alternative evaluation designs (e.g., synthetic control methods, stepped-wedge trials) to credibly estimate PQC impacts on maternal health outcomes.