Public hospital-based care for abortive events in Mexico: complication rates and socio-demographic factors, 2018-2022

Abstract

Background: Abortion-related complications are difficult to measure due to lack of standardized definitions and limited available data. We describe the proportion of abortive events that result in a documented complication in Mexico’s public sector hospitals. Methods: We used ICD-10 codes from Mexico’s hospital discharge system (2018-2022), Subsistema Automatizado de Egresos Hospitalarios (SAEH), to describe abortive events admitted to hospitals: complications for excessive bleeding, infection, embolism, and unspecified; patient socio-demographic and clinical characteristics; and municipality-level structural vulnerability. We estimate complications by pregnancy duration, describe types of complications, identify characteristics associated with the presence of a complication using multuvariable regression, and calculate complication rates (proportion of abortive event that result in a complication treated in a public sector hospital per 1,000 women of reproductive age) by state in 2022. Findings: There were 399,405 abortive events that received hospital-based care in Secretaria de Salud (SS) hospitals between 2018-2022. Ninety-two percent had no complication reported. The adjusted predicted probability of a complication was higher among patients at > 13 weeks’ gestation (8.9%; 95% CI 8.1–9.7%) compared with ≤ 13 weeks (6.6%; 95% CI 6.0–7.2%). Higher parity, care at a tertiary hospital, and high marginalization at place of residence were positively associated with presence of a complication. States with higher complication rates are primarily in the central and southern regions. Conclusions: In Mexico, 92% of patients who seek care for all abortive events (induced, spontaneous, post-abortion) in SS hospitals have no complications. Marginalized patients are more likely to have a complication and to seek care at later pregnancy durations. Routinely conflating care-seeking and complications leads to overestimates of the risk of abortion.