Objective:

There is limited access to neurological care in the United States for underserved and minority patients. Uninsured patients are more likely to have life threatening neurological conditions and complications that go untreated or undertreated. We evaluated the demographic and clinical information of the uninsured population receiving neurologic care at the Birmingham Free Clinic (BFC) in Pittsburgh, Pennsylvania. 

Background:

The BFC was established in Pittsburgh in 1994 for underserved patients, and evolved into a clinic that provides primary care, specialty care, pharmacy, and social work services to uninsured individuals. The Neurology Clinic at BFC was established in 2018 and is staffed on a volunteer basis.  

Design/Methods:

We conducted a descriptive, retrospective analysis of electronic medical record data of Neurology patient visits to the BFC from April 2023 to October 2024. We reported demographic and clinical information of this population including age, sex, race, ethnicity, primary language spoken, chief complaint, and diagnosis. 

Results:

A total of 39 patients’ charts were reviewed for this information. The average age of patients seen in this period was 39.6 years (range: 1.5-82 years). Languages spoken included Spanish (48.7%), English (33.3%), Russian (5.1%), Turkish (2.6%), Portuguese (2.6%), Arabic (2.6%). Reported races included White (38.5%), Black (30.8%), Asian (5.1%), other (10.3%), undisclosed (10.3%).  Of these visits, a total of 54 complaints were reported, most commonly Headache (27.8%), Seizure (25.9%), and Dizziness (5.6%). Common diagnosis given included Epilepsy (21.6%), Migraine (15.7%), Post-concussional Syndrome (5.9%) with additional diagnoses made including Neuropathy (3.9%), Parkinson Disease (3.9%), Amyotrophic Lateral Sclerosis (2.0%), and Functional Neurologic Disorder (2.0%).  

Conclusions:

Reporting demographic and clinical information can help providers in similar settings understand language and cultural barriers, create feasible diagnostic and treatment algorithms, and create targeted educational materials for an uninsured population. We hope to expand upon these results by including more patients and reporting additional vital information.