Data Quality Assessment to Improve Tuberculosis Reduction Program Performance in Coast Region, Tanzania

Abstract

Data quality assessment is central in improving program performance. Reducing TB pandemic transmission is challenging in the global south. The success of interventions to address the pandemic depends upon the availability of sound and reliable data. This study applied a mixed research design to investigate the influence of data quality assessment on the performance of TB reduction program. We interviewed staff of several facilities composed of Directly Observed Treatment (DOT) nurse in-charge, and TB coordinators, among others. We reviewed various TB-related documents and used key informant interviews and observation to collect data from selected health facilities. The findings indicated that the performance of the programs can be determined if the data reported meets the five data quality standards, and present accurately what is done at the facility level. Facilities with accurate, reliable and timely data enable the reduction of TB cases through informing adequate treatment to avoid spreading infection to the wider population unlike those with unreliable data. In this study, most of the health facilities data under-reported the number of TB cases, thus leading to poor program performance. We argue that, to improve program performance, data provided from different facilities should meet the five quality standards. The study recommends regular training of DOT nurses and improvement of monitoring and evaluation systems.