Text analysis of data collected from online forum conversations reveals that Social Security Disability Insurance (SSDI) applicants and recipients share concerns and confusion about the application, appeal, and continuing disability review (CDR) rules and policies. For example, many SSDI customers (e.g., veterans) do not understand how the substantial gainful activity (SGA) rule is applied. These applicants also experience significant differences across program offices and geographic regions on the application of rules and/or the interpretation of these rules (e.g., how disability, medical improvement, or SGA is defined). Preliminary results from Year 2 project suggest that confusions about how SSDI rules are interpreted and applied significantly contribute to high SSDI rejection and appeal rates. This study intends to build upon Year 2 project findings to provide insights on designing effective communication strategies to reduce confusions and aid in improving customer service experiences and welfare. Specifically, the study aims to: 1) identify the major areas of confusion about SSA rules and decision criteria using a machine-learning hybrid approach for Natual Language Processing (NLP) and text analytics, and 2) evaluate the impact of how and when SSA customers obtain such information that impact their subsequent interpretation of this information.
WI21-01: Using Online SSDI Conversations to Improve Communication and Outreach