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Tuberculosis Research and Treatment
Volume 2012 (2012), Article ID 481230, 11 pages
http://dx.doi.org/10.1155/2012/481230
Research Article

Innovative Quality-Assurance Strategies for Tuberculosis Surveillance in the United States

Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and Tuberculosis Prevention, Centers for Disease Control and Prevention (CDC), Mailstop E-10, 1600 Clifton Road, Atlanta, GA 30033, USA

Received 28 November 2011; Revised 17 February 2012; Accepted 20 March 2012

Academic Editor: Kashef Ijaz

Copyright © 2012 Lilia Ponce Manangan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Introduction. The Centers for Disease Control and Prevention (CDC)’s National Tuberculosis Surveillance System (NTSS) is the national repository of tuberculosis (TB) data in the United States. Jurisdictions report to NTSS through the Report of Verified Case of Tuberculosis (RVCT) form that transitioned to a web-based system in 2009. Materials and Methods. To improve RVCT data quality, CDC conducted a quality assurance (QA) needs assessment to develop QA strategies. These include QA components (case detection, data accuracy, completeness, timeliness, data security, and confidentiality); sample tools such as National TB Indicators Project (NTIP) to identify TB case reporting discrepancies; comprehensive training course; resource guide and toolkit. Results and Discussion. During July–September 2011, 73 staff from 34 (57%) of 60 reporting jurisdictions participated in QA training. Participants stated usefulness of sharing jurisdictions’ QA methods; 66 (93%) wrote that the QA tools will be effective for their activities. Several jurisdictions reported implementation of QA tools pertinent to their programs. Data showed >8% increase in NTSS and NTIP enrollment through Secure Access Management Services, which monitors system usage, from August 2011–February 2012. Conclusions. Despite challenges imposed by web-based surveillance systems, QA strategies can be developed with innovation and collaboration. These strategies can also be used by other disease programs to ensure high data quality.