Economic precarity, costs, and continuity of mental health care - PROJECT SUMMARY/ABSTRACT Candidate: Catherine Ettman, PhD, is an early career mental health services researcher. Her long-term career objective is to become an independent investigator and national expert on the role of different assets in shaping mental health and mental health services utilization towards the end of reducing inequities. Research Context: Depression is common, costly, and its burden is felt unequally. Treatment for depression can be effective but is hampered by interruptions in care, such as appointment non-adherence, or no-show. Reducing appointment no-show is a feasible and cost-efficient way to improve patient care and outcomes. Specific Aims: 1) To test whether higher out-of-pocket healthcare costs increase psychiatric appointment no- show; 2) To estimate the causal effect of clinical operations features (such as telehealth and appointment reminders) on no-show and whether the effect varies across patients with access to different financial assets; 3) To identify the financial and other factors that most strongly predict psychiatric appointment no-show. Research Plan: Using electronic health records (EHR) in a cohort of 23,420 patients with depression from the Johns Hopkins Medicine Precision Medicine Center of Excellence on Mood Disorders, Dr. Ettman will comprehensively examine the effect of financial and clinical operations features on psychiatric no-show in patients with depression to inform intervention. In Aim 1, Dr. Ettman will use an instrumental variables approach to estimate the effect of higher out-of-pocket costs on subsequent appointment no-show, leveraging variation in facility fees, external to the patient and induced by Maryland state policy, as an instrument. In Aim 2, Dr. Ettman will use contemporary matching approaches such as full propensity score matching and doubly robust methods to estimate the causal effect of clinical operations features (such as telehealth and appointment reminders) on psychiatric appointment no-show and she will assess if the effect varies across patients with access to different financial assets. In Aim 3, Dr. Ettman will use modern prediction models including random forest and Lasso to determine which financial and other factors predict psychiatric no-show. Career Development Plan: Dr. Ettman will develop expertise in 1) causal design, including instrumental variable analysis and contemporary matching approaches; 2) health informatics, specifically advanced prediction models; and 3) ethical and practical health system clinical operations. Dr. Ettman’s training will be supported by close mentorship, advanced didactic coursework, and career development activities. Research Goals: This proposal builds on Dr. Ettman’s track record of successful publication and project management, a highly involved primary mentor and expert mentorship team, and strong institutional support, while providing protected time for training. Together, this body of work will identify implementable policy recommendations that improve population mental health.
