Transforming Maternal Mental Health Care Using Innovative Digital Solutions for the Intermountain West
The overall objective of this pilot study is to assess the feasibility of a RCT comparing Lōvu-augmented with usual prenatal care at UU. This would be a critical next step toward our long-term goal to identify technology-based interventions to improve maternal mental health in the Intermountain West. Our central hypothesis is that Lōvu will be both feasible and have high patient and clinician satisfaction, and that Lōvu-generated data will be a promising substrate for AI-based mental health risk stratification.
Collectively, perinatal mental health disorders impact 20% of pregnancies in the U.S. and are the leading cause of pregnancy-related mortality, contributing to 23% of deaths. In the U.S., 50-75% of perinatal depression (PND) is undiagnosed and PND is untreated in nearly 85%. This is a result, in part, of the systematic underfunding of investigations into maternal mental health. The critical relevance of this reality for "Women Across the Lifespan" could not be more pressing than in Utah and the Intermountain West, where expanding maternity care deserts limit access to mental health care, and suicide rates are 57% above the national average. The traditional prenatal care paradigm does not address maternal mental health needs. It utilizes relatively wide intervals between prenatal visits during the first three quarters of pregnancy-a time of substantial need for education, psychosocial support, and mental health services-only to culminate in a 'care cliff' postpartum, when the risk of mental health crises and maternal mortality is highest. Technology has enabled remote visits, but telehealth implementations remain anchored to the traditional prenatal care model and consist of two elements: virtual rather than in-person visits, and EHR-based electronic messaging. This amounts to a "worst of both worlds", in which diluted personal connection and the escalating burden of e-messaging contribute to clinician burnout while the core deficiencies of the traditional paradigm remain. Thus, there is a critical need for novel approaches to prenatal care that more fully deliver on the promise of technology to 1) increase patient access and support, 2) reduce clinician burnout, and 3) improve maternal and newborn outcomes. Aim 1: Assess the feasibility of a randomized, controlled trial comparing usual vs. Lōvu-augmented prenatal care among N=50 pregnant patients. Feasibility will be defined as the successful recruitment of \> 50% of patients we approach and 90% participant retention for the 12-month study period. Aim 2: Assess mental health screening completion, care utilization, and user satisfaction in Lovu-augmented vs usual care. We will assess the following outcomes: for clinical care: participant completion of PHQ-9 (PND), GAD-7 (anxiety), NIDA quick screen (substance use), and time to mental health referral and first visit; for utilization: burden of patient-generated e-messages and phone calls to the UU MFM clinic; satisfaction: telehealth usability questionnaire12 and telemedicine satisfaction questionnaire;13 system usability scale.14 Aim 3: Utilize pilot study data to inform the future development of a novel AI-based mental health early warning and referral system. We will 1) harmonize data from the user app, digital sensors, UU electronic health records (EHR) and 2) develop streamlined data transfer and harmonization workflows.
Inclusion Criteria: * Pregnant people receiving care at University of Utah Clinics * Less than 14 weeks gestation at enrollment
Exclusion Criteria: * Patients enrolled in other studies utilizing remote monitoring
[{"measure":"Feasibility Outcomes","timeFrame":"12 Months"}]