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Routine Data Quality Assessment Tool (RDQA): Guidelines for Implementation

Authors:
The Global Fund to Fight Aids, Tuberculosis and Malaria | PEPFAR | USAID | World Health Organization (WHO) | UNAIDS | MEASURE Evaluation
Year Published:
2008
Resource Type:
Tools & Manuals
Language:
English

National Programs and donor-funded projects are working towards achieving ambitious goals related to the fight against diseases such as Acquired Immunodeficiency Syndrome (AIDS), Tuberculosis (TB) and Malaria. Measuring the success and improving the management of these initiatives is predicated on strong Monitoring and Evaluation (M&E) systems that produce quality data related to program implementation.

In the spirit of the “Three Ones”, the “Stop TB Strategy” and the “RBM Global Strategic Plan”, a number of multilateral and bilateral organizations have collaborated to jointly develop a Data Quality Assessment (DQA) Tool. The objective of this harmonized initiative is to provide a common approach for assessing and improving overall data quality. A single tool helps to ensure that standards are harmonized and allows for joint implementation between partners and with National Programs.

The DQA Tool focuses exclusively on (1) verifying the quality of reported data, and (2) assessing the underlying data management and reporting systems for standard program-level output indicators. The DQA Tool is not intended to assess the entire M&E system of a country’s response to HIV/AIDS, Tuberculosis or Malaria. In the context of HIV/AIDS, the DQA relates to component 10 (i.e. Supportive supervision and data auditing) of the “Organizing Framework for a Functional National HIV M&E System”.

Two versions of the DQA Tool have been developed: (1) The Data Quality Assessment Tool for Auditing provides guidelines to be used by an external audit team to assess a Program/project’s ability to report quality data; and (2) The Routine Data Quality Assessment Tool is a simplified version of the DQA for auditing, allows Programs and projects to assess the quality of their data and strengthen their data management and reporting systems.