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TB Notes Newsletter

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No. 2, 2014

INTERNATIONAL RESEARCH AND PROGRAMS BRANCH UPDATES

Improving the Quality and Usage of TB Surveillance Data — Uganda

Background: The development and maintenance of robust national-level TB surveillance systems is a priority in TB control.1,2  Strong surveillance systems can be used to improve planning and monitoring of interventions and progress towards TB program targets, while weak surveillance systems can shroud or hinder programmatic successes. Nonetheless, maintaining quality TB surveillance data remains a challenge in many countries, with issues such as underreporting being widespread.2 This makes it difficult to recognize the true burden of TB and thus plan and provide the programs necessary for optimal TB control.

In Uganda, one of the world’s 22 high TB-burden countries,2 an evaluation using the World Health Organization’s Checklist of Surveillance Standards and Benchmarks identified gaps in national TB surveillance, namely high underreporting and lack of data use. To close these gaps and strengthen the national TB surveillance system, the Uganda National TB and Leprosy Programme (NTLP) collaborated with DTBE/IRPB and the African Field Epidemiology Network to develop and implement an intervention for all NTLP staff called TB Data – Improving Quality and Usage (TB-IQu).

Intervention: The Performance of Routine Information System Management (PRISM) framework3,4 guided the development of TB-IQu. The PRISM framework proposes that data quality and information use are affected by technical, organizational, and behavioral factors, all of which this intervention was designed to address. In addition, key principles for building improved health information systems were followed (e.g., focus on empowerment, local ownership, using existing infrastructure),5 while lessons learned in other health sectors were built upon.6,7 

On the technical side, systems and tools were created to prioritize data quality and usage. The format for data presentation at subnational quarterly TB meetings was revised to promote critical peer-reviews of data. To do this, a new, automated template was created to enable subnational staff to easily create and present basic time-series analyses of key TB epidemiologic and programmatic variables. As this new system relies on analyzing trends over time, unexplained changes highlight where reporting errors are likely. This increases the usefulness of data for subnational staff and encourages the responsible TB staff to examine suspect data. As a result, the quality of data that reach the central level improves.

On the organizational side, a systematic approach to data audits and checks was developed along with standard operating procedures (SOPs) for all data-related tasks.  To promote adherence, these SOPs are in the process of being organized in a desk guide for staff, with select SOPs to be displayed as posters for placement in relevant offices. 

On the behavioral side, a training-of-trainers workshop curriculum was designed to enable staff to practice using new tools and procedures and guide subnational TB staff to value the importance of quality data. To foster sustainable change, the workshop consists of group discussions and hands-on practice.

Initial results: TB-IQu rollout is ongoing. To date, the tools and processes of this intervention have been reviewed by various stakeholders and piloted among approximately 20 national and zonal (i.e., provincial) TB staff at a 3-day workshop in December 2013. Based on group evaluations, participants viewed this workshop to be successful at raising awareness of the need to increase the quality and use of data, especially at the subnational level. In particular, staff members were enthusiastic about using the new quarterly analysis template to analyze and present time-series analyses on subnational data. This was the first time they had used graphs to view their data and examine data over time. They were surprised to discover that this approach revealed inconsistent trends in their data, which were likely due to unrecognized problems with recording and reporting. These findings spawned lively group discussions on problems about and potential solutions for data quality.

Staff unanimously indicated that this training added meaning to the data they collected and enabled them to view and interpret data in new ways. In particular, they expressed strong interest in the quarterly analysis template because it allowed even those with minimal computer literacy to turn raw data into usable information. However, they said that additional training and simplification of the tool would be needed to ensure acceptance and use by all subnational staff.

Next steps: At this time, the Uganda NTLP is making plans to roll out TB-IQu to district-level staff. As this roll-out happens, IRPB will provide assistance in monitoring and improving the acceptance and viability of TB-IQu over time. Meanwhile, DTBE/IRPB is collaborating with programs in South Africa to adapt and implement TB-IQu, as it is anticipated that TB-IQu can be easily adapted for use in other countries that are also hoping to strengthen national TB surveillance and improve estimates of TB incidence.

For more information, contact Deanna Tollefson (vtu3@cdc.gov).

 

 

Reported by Deanna Tollefson, MPH
Div of TB Elimination

References

  1. World Health Organization. Definitions and reporting framework for tuberculosis – 2013 revision.  2013. Accessed on Feb 6, 2014 at http://apps.who.int/iris/bitstream/10665/79199/1/9789241505345_eng.pdf.
  2. World Health Organization. Global Tuberculosis Report 2012. Accessed on Jan 22, 2014 at http://www.who.int/tb/publications/global_report/en/.
  3. Aqil A, Lippeveld T, Hozumi D. PRISM framework: A paradigm shift for designing, strengthening, and evaluating routine health information systems. Health Policy Plann. 2009; 1-12.
  4. Hotchkiss D, Aqil A, Lippeveld T, and E Mukooyo. Evaluation of the Performance of Routine Information System Management (PRISM) framework: evidence from Uganda. BMC Health Serv. Res. 2010; 10:188.
  5. Health Metrics Network. Framework and Standards for Country Health Information Systems: Second Edition. World Health Organization 2008 June; pp. 42-44.
  6. Braa J, Heywood A, Sahay S. Improving quality and use of data through data-use workshops: Zanzibar, United Republic of Tanzania. Bull. World Health Organ 2012; 90:379-384.
  7. Mphatswe W, Mate K, Ngidi H, Reddy J, Barker P, Rollins N. Improving public health information: a data quality intervention in KawZulu-Natal, South Africa. Bull. World Health Organ 2012; 90:176-182.

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