Building toward a standard model for perinatal mental healthcare - Sheldrick, R. Christopher; Hansen, Megan Deichen; Cirino, Nicole H.; Kimmel, Mary; King, Courtney; Logan, Deirdre; Menke, Rena; Tabb, Karen (Frontiers in Psychiatry, 2025)
BackgroundHealthcare decision-making relies on models that synthesize complex components such as disease epidemiology, diagnostic accuracy, and treatment efficacy. A healthcare model serves as a framework to integrate health systems research, biological understanding, and diverse perspectives on health, enabling decision-makers to optimize access, quality, cost, and equity. The National Academy of Sciences, Engineering, and Medicine (NASEM) has underscored the need for a shared conceptualization in behavioral sciences to unify definitions and facilitate data synthesis. To achieve this, a standard model of perinatal mental healthcare is imperative.ObjectiveWe propose the development of a standard model of perinatal mental healthcare, analogous to the Standard Model of Particle Physics, which has guided scientific discovery by defining building blocks, highlighting knowledge gaps, and fostering interdisciplinary collaboration. A standard model for perinatal mental healthcare should function similarly—identifying key components, delineating evidence gaps, and inspiring critical inquiry.MethodsOur work is informed by our role as an advisory council supporting Perinatal Psychiatry Access Programs, which enhance healthcare systems by providing frontline clinicians with psychiatric consultation, training, and resources. These programs are designed to support evidence-based interventions across screening, therapy, and pharmacotherapy, and have been successfully implemented in multiple states and internationally.ConclusionEstablishing a robust standard model of perinatal mental healthcare is essential for addressing population-level mental health challenges. Furthermore, collaboration and governance structures for shared resources—akin to Elinor Ostrom’s principles of common-pool resource management—are essential for sustainability. Scientific advances in systems modeling, teamwork, and knowledge-sharing frameworks will be critical to developing an effective, widely accepted model.