MS CATCH: Closing the Gaps in Depression Care for People with MS by Closing the Information Loop
Abstract
Objectives and Rationale: The overall goal of this project is to improve care for depression in people with multiple sclerosis (MS). Over half of patients living with MS will experience depression. While there are a number of different effective treatments for depression, depression is often not addressed in routine clinical appointments. This is because depression is often not reported by patients, not screened for by doctors, and not treated according to guidelines or evidence. Further, doctors don t always consider all the other MS-related factors (fatigue, pain, work difficulties) that may impact a patient s mood. Patients sometimes experience difficulty following through on treatments due to difficulties with access, insurance, or finding specialists close to home. Our proposed solution is an app called MS CATCH that is designed to help increase communication between a patient and their doctor, to improve how depression is reported, addressed, and treated. Intervention: The project will involve three parts. In the first part, we will work with a broad group of stakeholders (patients, MS nurses and doctors, psychiatrists, MS advocacy group, and technology experts) to improve the MS CATCH app design. Feedback will be used to make sure diverse stakeholders find it useful, effective, easy to use, and likable. In the second part of the project, we will test the app over the course of one year with a diverse group of 125 people living with MS. In between appointments, patients will use the MS CATCH app to report their mood on a regular basis to their doctor. During appointments, doctors will review information captured by the app with the patient, as well as many other types of relevant information all assembled in one webpage: medications, other contributing factors (like poor sleep or decreased exercise, and resources such as MS talk therapists in the patient s community. Together they can make shared decisions about how best to treat any mood issues. Testing will help us understand how the tool is used, if it improves patient reporting and clinician treatment of depression, and ultimately if it leads to improvements in patient mood. In the third part, we will study which types of patients are most likely to use the app or benefit from it. What types of patients will it help, and how will it help them? The MS Clinic at the University of California San Francisco (UCSF) serves several thousand people with MS, who drive on average six hours to access MS care. At least 35 percent of these patients self-identify as being a racial or ethnic minority, and about half of them experience some depression. The average length of time between appointments is six months. Having an app designed to increase communication around depression so that symptoms can be addressed and treated in a timely manner, stands to benefit all patients, whether currently living with, or at risk of depression. We will enroll patients who are broadly representative of our clinical population in order to test the tool in as close to a real-clinic setting as possible. What are the potential clinical applications and benefits? MS CATCH is designed to gather information from the patient on a simple app on their personal device, and report this information in a dashboard that can be launched with one click from the electronic health record (EHR). The display will also include information not usually found in the EHR, such as data about the patient s community and local support resources. Together, this information can help patients self-manage, and clinicians tailor treatments, anticipate challenges, and make social and mental health referrals. What are the likely contributions of the proposed study to advancing MS patient care and quality of life? People with MS experience a number of bothersome symptoms that can cause or worsen depression. While there are effective treatments for depression, often patients do not report their sy
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210894
Entities
People
- Riley M Bove
Organizations
- United States Army
- University of California, San Francisco