Data quality audits should facilitate the independent identification of underlying issues, an understanding of the status of data quality, and the triggering of targeted investments to improve the situation. [...] 2.1 Data Quality determinants The quality of data is compromised from the outset of the data journey. [...] Page 4 of 17 Figure 2: Illustrative data quality interventions from data collection to Global Fund reporting Page 5 of 17 2.2 Global Fund Data Quality Improvement Framework and available tools The Global Fund Data Quality Improvement Framework is aligned with the forthcoming WHO Country Health Statistics Quality Assurance Framework for routine and non-routine data. [...] However, it is of greater importance to direct attention to the implementation of the recommendations stemming from the periodic data audits, which should inform the development of a DQIP or data quality strategy. [...] The analysis of progress and data quality at all levels, from the health facility to the national level, should inform the improvement of program implementation and data quality.
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- 17
- Published in
- Switzerland
Table of Contents
- Global Fund Data Quality Improvement Framework 1
- Date published 1
- Executive summary 2
- 1. Context 3
- Country Health Statistics Quality Assurance Framework 3
- 2. Systemic Data Quality Investments 3
- Country Health Statistics Quality Assurance Framework for routine and non-routine data 6
- Data Quality Improvement Plan DQIP 8
- DHIS2 data quality toolkit 8
- WHO Data 8
- Quality Tool 8
- RDQA methodology 9
- 3. Updated data quality metrics 10
- 4. Complementary Global Fund assurance options Data System spot-checks 11
- 5. Roles and responsibilities 11
- References 13
- Global Fund resources 13
- Partner resources 13
- Annex 1 Decision tree to guide routine data quality interventions and investments including LFA assurance options 14
- Annex 2 Funding Request and reprogramming guidance for data quality essentials investments in High ImpactCore portfolios 15
- 1 Data quality essentials if not covered by other funding sources 15
- 1.1. Periodic revision of data collection and reporting tools 1.1.1. variablesindicators strict minimum 15
- 1.1.2. simplified ergonomic data 15
- 1.1.3. Update guidance 15
- 1.1.4. Configure 1.1.5. Printing and distribution 1.1.6. digital tools 15
- 1.2. Staff training and mentoring 15
- 2 Data quality assurance mechanism 15
- 2.1. Monthly health facility monitoring meetings 15
- 2.2. Quarterly district level data validation and monitoring meetings 16
- 2.3. Six-monthly regional meetings 16
- 2.4. Annual national meetings 16
- 2.5. Data quality control activities 2.5.1. 16
- 2.5.2. 16
- 2.5.3. 16
- 2.5.4. 16
- 3 Data Quality incentives 16
- Annex 3 Data quality metrics by source and measurement frequency 17
