Evaluating the Referral Process among Immigrants with Tuberculosis

Abstract

Background: The Centers for Disease Control & Prevention (CDC) Division of Global Migration and Quarantine (DGMQ) has 20 quarantine stations (QS) across the United States (U.S.). Each QS provides consultation and referral services to foreign born persons with tuberculosis (TB) class B conditions who intend to reside in the U.S. After arrival in the U.S., immigrant medical packets are reviewed and packets with TB class B conditions are sent from each QS to the CDC Electronic Disease Notification (EDN) system from which they are forwarded to State and Local Health Departments for referral for follow-up. This study analyzed Philadelphia International Airport (PHL) Quarantine Station’s experience with the CDC EDN system and the immigrant referral process. Methods: All data used for this project were obtained from the EDN database maintained by the PADOH. We obtained EDN records for immigrants who had TB class B conditions as a result of the EDN notification process. Password-protected spread sheet with de-identified EDN evaluation follow-up sheets provided by Pennsylvania Department of Health (PADOH) were decoded, analyzed, and defined. EDN immigrants’ data were analyzed to determine the extent of any discrepancies in the referral process at PHL QS and compare them with other QS referral process by use of simple statistical analysis. Frequencies, means, modes and medians explored if the port of entry into the US correlates to follow-up outcomes. Results: A total of 627 immigrants with TB conditions entered Pennsylvania 2009 and 2010. A total 49 immigrants with a TB condition arrived PHL. Of these 49 immigrants, 8 (16.3%) followed-up at local health departments for further medical evaluation. The average duration between date of arrival and follow-up for these immigrants was 74 days. For immigrants entering PA from other QS, 153 (24.4%) followed-up. Conclusions: The EDN system needs much improvement. The low follow-up rates and the prolonged time for follow-up are inadequate. Data entry is low priority where resources are low, making follow-up data entry into EDN unstable. Providing guidance and training for stakeholders to use EDN properly and better information technology can improve its efficiency.%%%%M.P.H., Public Health – Drexel University, 2011