Primary Immune Deficiency (PID) is a debilitating condition that affects one in 1,200 persons in the US. Growing evidence demonstrates that PID is underdiagnosed in the US and globally. Of note, prior to the implementation of population-wide newborn screening, severe combined immunodeficiency (SCID) was estimated to affect approximately 1 in 100,000 infants, with ~90% of identified cases occurring in non-Hispanic Whites3. Following the introduction of newborn screening, the observed incidence of SCID nearly doubled and cases were found to occur at similar rates across different ethnic groups5, suggesting significant disparities in diagnosis prior to universal screening. Underdiagnosis of PID is not confined to SCID, most of which cannot yet be detected through newborn screening. Delay in the treatment of PID can result in serious health consequences, including irreversible organ damage and death. There is therefore an urgent need to address gaps in the diagnosis of PID. Our long-term goal is to improve timely diagnosis and treatment of PID. To address disparities in the diagnosis of PID, we propose the following specific aims: (1) Identify patterns of diagnostic disparities in PID; (2) Identify factors contributing to diagnostic disparities in PID; and (3) pilot a targeted educational intervention aimed at increasing awareness of PID and the risk factors associated with its underdiagnosis. We will combine analyses of electronic health record (EHR) data (Aim 1) with qualitative analysis of patients’ experience and real-world perspectives from healthcare providers to understand the contributing factors of delayed PID diagnosis (Aim 2). Additionally, we will apply advanced machine learning analysis as an innovative approach to enable a more comprehensive understanding of the patterns of diagnostic delay. PID is a complex group of diseases with highly variable clinical manifestations. We anticipate that the application of machine learning methods to EHR data can facilitate identification of under-recognized patterns of diagnostic delay and will enable us to learn from large clinical datasets in a scalable manner. Integrating knowledge from these analyses, we will then develop and evaluate an educational outreach program targeting healthcare providers to raise awareness of PID and the risk factors associated with its underdiagnosis (Aim 3). The study will be conducted at 2 major healthcare systems in Massachusetts: Beth Israel Lahey Health and Boston Medical Center. This body of work represents the first systematic effort to investigate the patterns and contributing factors of diagnostic disparities in PID. The proposed educational outreach program will be the first educational initiative aimed at addressing PID diagnostic disparities in the US, and will provide a foundation towards our longer-term goal of designing and developing a regional/national educational program to improve diagnosis of PID.