Background: Three indicators of severe maternal morbidity (SMM) available in US birth certificate data are increasingly used in research, yet prior studies suggest they are poorly ascertained. It is unclear whether low validity of these data threatens causal inference in evaluations of policies or shocks that vary across states and over time, including abortion bans enacted after the Supreme Court’s Dobbs decision.

Methods: Using birth certificate and hospital discharge data from 12 states (2018–2021), we assessed data quality for three SMM indicators (hysterectomy, blood transfusion, and eclampsia) and a composite measure and compared state-year trends across six states that subsequently imposed abortion bans shortly after the Dobbs decision and six that did not, including tests of the parallel trends assumption.

Results: Compared with hospitalization data, birth certificates under-ascertained hysterectomy, blood transfusion, and the composite measure while over-ascertaining eclampsia. Composite SMM rates appeared higher in abortion-ban states using birth certificate data but were similar or lower in hospitalization data. Over time, birth certificate ascertainment improved in states with bans but remained flat elsewhere, potentially introducing data artifacts. Violations of the parallel trends assumption were detected in hospitalization but not birth certificate data.

Conclusions: Reliance on birth certificate data for policy evaluation can produce erroneous inferences.