A multi-level explanatory-sequential mixed-methods study of perinatal toxicology practices in New York State: Protocol
Abstract
Objective Maternal morbidity and mortality (MMM) rates from drug overdoses have increased, especially among pregnant and postpartum women aged 35–44. However, there is limited understanding of how current toxicology testing practices are implemented in hospital settings and how well they support, or undermine, linkage to care. The goal of the study is to understand variations in toxicology testing use among pregnant and postpartum women, explore hospital- and individual-level differences, and assess outcomes. Methods Using the Socio-cultural Framework for the Study of Health Service Disparities (SCF-HSD) we will perform a mixed-methods study to understand testing policies and practices in NY State. Aim 1 will employ multilevel statistical models using New York State Medicaid claims data (2021–2024) to identify predictors of perinatal toxicology testing and characterize hospital-level variation across hospitals. Aim 2 will involve one-on-one interviews with hospital administrators and clinical staff to document and analyze testing policies and practices, capturing diverse perspectives on testing rationales, attitudes, and adherence. Aim 3 will integrate quantitative and qualitative evidence through a mixed-methods design, incorporating perspectives of individuals with lived experience, via focus group sessions to inform and refine hospital policy recommendations. Discussion Our findings will inform how to improve disparities in toxicology testing for pregnant and postpartum women. Addressing these challenges requires shifting emphasis toward standardized, evidence-based toxicology testing protocols, strengthening pathways to supportive services, and advancing policy reforms that reduce stigma and inequities in care.
Article Details
Authors (11)
Sugy Choi
Elizabeth Knopf
Erin Kim
Biodesign Center for Mechanisms of Evolution, Arizona State University
Charles J. Neighbors
Carolyn A. Berry
Erinn Hade
Chau Trinh-Shevrin
Mishka Terplan
Neil S. Seligman
David J. Garry
Jennifer McNeely