Perinatal mental health in low-income urban and rural patients: The importance of screening for comorbidities

Developing consensus to enhance perinatal mental health through a model of integrated care: Delphi study

Perinatal mental illness is an important public health issue, with one in five birthing persons experiencing clinically significant symptoms of anxiety and/or depression during pregnancy or the postpartum period. The purpose of this study was to develop a consensus-based model of integrated perinatal mental health care to enhance service delivery and improve parent and family outcomes. We conducted a three-round Delphi study using online surveys to reach consensus (≥75% agreement) on key domains and indicators of integrated perinatal mental health care. We invited modifications to indicators and domains during each round and shared a summary of results with participants following rounds one and two. Descriptive statistics were generated for quantitative data and a thematic analysis of qualitative data was undertaken. Study participants included professional experts in perinatal mental health (e.g., clinicians, researchers) (n = 36) and people with lived experience of perinatal mental illness within the past 5 years from across Canada (e.g., patients, family members) (n = 11). Consensus was reached and all nine domains of the proposed model for integrated perinatal mental health care were retained. Qualitative results informed the modification of indicators and development of an additional domain and indicators capturing the need for antiracist, culturally safe care. The development of an integrated model of perinatal mental health benefitted from diverse expertise to guide the focus of included domains and indicators. Engaging in a consensus-building process helps to create the conditions for change within health services.

Text And Telephone Screening And Referral Improved Detection And Treatment Of Maternal Mental Health Conditions

Effective screening and referral practices for perinatal mental health disorders, perinatal substance use disorders (SUDs), and intimate partner violence are greatly needed to reduce maternal morbidity and mortality. We conducted a randomized controlled trial from January 2021 to April 2023 comparing outcomes between Listening to Women and Pregnant and Postpartum People (LTWP), a text- and telephone-based screening and referral program, and usual care in-person screening and referral within the perinatal care setting. Participants assigned to LTWP were three times more likely to be screened compared with those assigned to usual care. Among participants completing a screen, those assigned to LTWP were 3.1 times more likely to screen positive, 4.4 times more likely to be referred to treatment, and 5.7 times more likely to attend treatment compared with those assigned to usual care. This study demonstrates that text- and telephone-based screening and referral systems may improve rates of screening, identification, and attendance to treatment for perinatal mental health disorders and perinatal SUDs compared with traditional in-person screening and referral systems. System-level changes and complementary policies and insurance payments to support adoption of effective text- and telephone-based screening and referral programs are needed.

Mapping high-risk clusters and identifying place-based risk factors of mental health burden in pregnancy

Purpose

Despite affecting up to 20% of women and being the leading cause of preventable deaths during the perinatal and postpartum period, maternal mental health conditions are chronically understudied. This study is the first to identify spatial patterns in perinatal mental health conditions, and relate these patterns to place-based social and environmental factors that drive cluster development.

Methods

We performed spatial clustering analysis of emergency department (ED) visits for perinatal mood and anxiety disorders (PMAD), severe mental illness (SMI), and maternal mental disorders of pregnancy (MDP) using the Poisson model in SatScan from 2016 to 2019 in North Carolina. Logistic regression was used to examine the association between patient and community-level factors and high-risk clusters.

Results

The most significant spatial clustering for all three outcomes was concentrated in smaller urban areas in the western, central piedmont, and coastal plains regions of the state, with odds ratios greater than 3 for some cluster locations. Individual factors (e.g., age, race, ethnicity) and contextual factors (e.g., racial and socioeconomic segregation, urbanity) were associated with high risk clusters.

Conclusions

Results provide important contextual and spatial information concerning at-risk populations with a high burden of maternal mental health disorders and can better inform targeted locations for the expansion of maternal mental health services.