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Updated: Aug 26, 2026

The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
Published on: August 11, 2008
Optimizing use of data and evidence-related tools to complement routine surveillance systems for tuberculosis program
Rachel M Fiorillo1, Eveline Klinkenberg2, Christina Braccio3
1Infectious Disease Department, CDC Foundation, Atlanta, GA, United States.
Background:
Challenges and gaps with routine tuberculosis (TB) data and surveillance systems are well-known. To address them, numerous TB data and evidence-related tools (e.g. surveys, assessments) have been developed to help countries collect, analyze, and use TB-related data. The "TB Data Optimization Project" aimed to assess the use and usefulness of these tools and propose best practices.
Methods:
Phase one of this mixed-methods project included structured key informant interviews (KIIs) with TB data experts, literature review, and mapping tools' indicators and metrics. Phase two consisted of case studies in five countries (Ethiopia, Kenya, Pakistan, Uganda, and Vietnam). Structured KIIs and a use case discussion were conducted with TB program staff and partners in each country, and TB-related documents were reviewed. Phase three was an online survey for national TB programs. Qualitative data were recorded, transcribed, coded, and inductively analyzed. Quantitative data were analyzed descriptively. Findings were triangulated and summarized into key themes.
Results:
Seventy-two KIIs were conducted, 42 countries completed surveys, and 212 documents were reviewed. Six key themes emerged: usefulness, opportunities and challenges with planning and implementation, technical assistance and financial support, timing and coordination, motivating factors for implementation, and the role of tools in relation to routine data systems. The tools provide critical information and most were considered worth the investment. Challenges include suboptimal implementation of the recommendations from the tools, poor timing and coordination of implementation, and insufficient capacity building. A set of best practices was developed.
Conclusion:
While the long-term goal is to strengthen and integrate routine data systems, TB data tools currently play an important role in filling gaps. Findings from this project provide considerations for optimal use of TB data tools; however, there is still need for further guidance on selecting the most critical tools to fill gaps during TB programmatic and strategic planning.
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