Modeling the Causal Pathways Between Multiple Sclerosis and Depression

• Activity Number: 294
• Type: Topic Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Mental Health Statistics Section
• Author(s): Douglas Gunzler*+
• Companies: Case Western Reserve University
• Keywords: structural equation modeling ; mediation analysis ; factor analysis ; electronic health records ; patient-reported outcomes

Abstract

While multiple sclerosis (MS) patients commonly experience depressive symptoms, clinicians cannot reliably distinguish the indirect pathways through which different trajectories of MS leads to depression. In this talk, Structural Equation Modeling (SEM)-based approaches will be discussed for untangling the diagnostic overlap and causal pathways between MS, as defined by type and baseline time since diagnosis, and depression using the Knowledge Program (KP) at the Cleveland Clinic's Neurological Institute data base. SEM is a very general technique combining complex path models with latent (unobserved) variables. The KP links patient-reported depression (via the PHQ-9) responses to the EPIC EHR and provides a powerful opportunity to study and improve patient care and clinical research. SEM is a very appropriate approach to handing the latent variables, causality questions and irregular follow-up times in the KP data base.