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Background: Recent systematic review (Moore Simas et al., 2018) findings suggest integrating depression care into obstetric practice is feasible, effective, and acceptable, yet barriers to treating depression include inadequate referral resources, as well as inadequate care coordination and follow-up. To address maternal mental health and improve early neonatal health outcomes, more research is needed to understand the potential harms and benefits of behavioral health (BH) and obstetric care integration. Study Overview: This retrospective analysis will use electronic medical record patient data from a patient centered medical home (PCMH) in an urban setting in the southwestern U.S. that implements a full collaboration BH model. The purpose of the study is to examine whether an integrated BH care model delivered within an obstetric primary care (PC) setting is associated with improved maternal health behaviors, neonate’s gestational age, and birth weight, in pregnant women found at-risk for depression. Methods: Potential participants for this retrospective study were selected using convenience sampling based on women that received prenatal care, were administered the EPDS, and had information was placed in their EMR between October 2016 and July 2020. The sample is a total of 7,098 participants that were screened. A set of covariates related to maternal health, economic, and social factors were included in the model to control for their potentially confounding influence. Analysis Plan: Logistic regression will be used for binary dependent variables and ordinary linear regression for continuous dependent variables. Covariates will also be included in the analyses. Implications: This study will contribute to the limited integrated obstetric PC and BH literature that examines relationships between maternal depression, infant gestational age and birth weight. The findings from this study may help community health professionals understand how maternal depression relates to patterns of prenatal care initiation and BH utilization. Study Feasibility: There is a high likelihood that the study will be completed prior to the conference given the use of an archival data set. The data set has been de-identified, and therefore meets criteria for exempt human subjects’ research. Data preparation and preliminary analysis will begin November 2020. The large sample size increases the likelihood that there are sufficient cases to conduct planned analyses. A power analysis suggested a sample size of 81 is needed to detect a small partial relationship (Cohen’s f 2 = 0.10) with 80% statistical power using an alpha level of .05. The current study sample size is sufficient to detect the anticipated relationship between the outcomes.
Georgette Richardson, University of Houston
Presenting Author
Milena Keller-Margulis, University of Houston
Non-Presenting Author
Stephanie Chapman, Baylor College of Medicine
Non-Presenting Author
Hanjoe Kim, Univerisity of Houston
Non-Presenting Author
Sarah S. Mire, Baylor University
Non-Presenting Author
Faunda Armstrong, Baylor College of Medicine
Non-Presenting Author