Predictors of Clinical Appointment Attendance for Individuals with Serious Mental Illness and Diabetes

• Activity Number: 402
• Type: Invited
• Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Mental Health Statistics Section
• Author(s): Douglas Gunzler*
• Companies: Case Western Reserve University
• Keywords: Adherence ; Predictive Models ; Electronic Health Records ; Serious Mental Illness ; Diabetes

Abstract

We fit statistical models to determine factors associated with behavioral intervention attendance and outpatient clinic appointment show rate. This exploratory study focused on a population in which delivering effective personalized care is difficult. Specifically, we evaluated 200 individuals with serious mental illness (SMI) and a co-morbid physical health condition, diabetes mellitus (DM) from a NIMH-funded randomized controlled trial. A series of generalized linear mixed effects and weighted logistic regression models were used to identify baseline covariates predicting individual level attendance at study sessions and outpatient clinic appointments. Outpatient clinic appointment show rate was evaluated both retrospectively and prospectively using electronic health records to address any issues with reverse causality. Covariates included measures of demographics, social support, disease knowledge, physical health, mental health, self-efficacy, anticipated attendance and transportation.