Disentangling Multiple Sclerosis-Associated Fatigue and Depression: Methods to Improve Clinical Research and Care

• Activity Number: 492
• Type: Topic Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Social Statistics Section
• Author(s): Douglas David Gunzler*+
• Companies: Case Western Reserve University
• Keywords: structural equation modeling ; factor analysis ; electronic health records ; multiple sclerosis ; depression ; fatigue

Abstract

While multiple sclerosis (MS) patients commonly experience depressive symptoms, clinicians cannot reliably distinguish the roles of MS-associated fatigue and depression in patient-reported fatigue. In this talk, Structural Equation Modeling (SEM)-based approaches will be discussed for developing and evaluating an adjusted depression score for MS patients accounting for overlap of depression and MS-associated fatigue symptoms using the Knowledge Program (KP) at the Cleveland Clinic's Neurological Institute data base. 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. Disentangling the overlap of fatigue in depression and MS-related fatigue will help clinicians prevent over or under prescribing anti-depressants and fatigue and MS medication, providing better tailored care.