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CAP-Malaria Project, Burma 9 – 13 February 2015 Data Quality Assessment (DQA)

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Presentation on theme: "CAP-Malaria Project, Burma 9 – 13 February 2015 Data Quality Assessment (DQA)"— Presentation transcript:

1 CAP-Malaria Project, Burma 9 – 13 February 2015 Data Quality Assessment (DQA)

2 Presentation Outline Purpose of the DQA Methodology Preliminary findings Recommendations

3 DQA Purpose Verify the quality of reported data for key indicators at selected sites; and Assess the ability of data management systems to collect and report quality data.

4 Methodology Select indicators and service delivery sites to be assessed, Assess the ability of data management systems to collect and report quality data, Assess general M&E system and M&E capacity to identify overarching system available to support quality data, and Verify the quality of reported data for key selected indicators at selected sites

5 Selected Reporting Period Fiscal Year 2014 (1 Oct. 13 – 30 Sep. 14) or Year 3 of CAP-Malaria Project

6 Selected Indicators 1.Number of health workers trained in case management with artemisinin-based combination therapy (ACTs) with USG funds; 2.Number of health workers trained in malaria laboratory diagnostics (rapid diagnostic tests (RDTs) or microscopy) with USG funds; 3.Number of ACTs treatments purchased in any fiscal year with USG funds that were distributed in this reported fiscal year; 4.Number of RDTs purchased in any fiscal year with USG funds that were distributed in this reported fiscal year; and 5.Number of insecticide treated nets (ITNs) purchased in any fiscal year with USG funds that were distributed in this reported fiscal year.

7 Selected sites CAP-Malaria Yangon Office Tanintharyi CAP-Malaria Dawei Office Kywe Chan Village, and Win Ka Phaw Village in Thayetchaung Township Kayin CAP-Malaria Hpa-an Office CAP-Malaria Hlaing Bwe Office Kawt Ka Yet Kyun Village

8 Preliminary Findings (1) – M&E structure, roles and capacities Clearly assigned staff to M&E activities, including data collection, recording, verification and reporting. Clear data flow how data is processed and transferred into a system at each different level. M&E capacities varies among CAP-M staff.

9 Preliminary Findings (2) – M&E guidelines, indicator definitions and data collection tools Draft M&E plan is available, but not fully used by field staff. Not fully understanding of operational indicator definitions (e.g., number of people trained, what to be counted, and disaggregation). Using standard data collection tools across sites. DQA team found errors and incompleteness of the filled data collection forms.

10 Preliminary Findings (3) – Data management, verification and internal DQA process Numerous data in Excel database, requiring labor intensive. Changes have been made periodically. Clearly assigned staff for data verification, but the process should be done properly. Errors in recording found at all sites. Data properly stored and readily available, but not all. Protection of data both paper-based records and computerized database is not sufficient.

11 Preliminary Findings (4) – Reporting system and process Clear line and schedule for reporting. Uncontrollable external factors (e.g., weather, internet connection) may affect timeliness of reporting. Procedures to avoid double counting issues is not exist.

12 Preliminary Findings (5) – Data analysis and utilization A lot of process and output data are collected. Data were not being systematic analyzed and utilized.

13 Preliminary Findings (6) – Verification of reported data Source: SCI, 2014

14 Preliminary Findings (7) – Verification of reported data Source: SCI, 2014

15 Preliminary Findings (8) – Verification of reported data Source: URC, 2014

16 Preliminary Recommendations Closer collaboration between URC and partner agencies to ensure common understanding of M&E requirements and utilization of data collection forms. Provide supportive supervision/ mentoring on M&E activities and ensure staff have a clear understanding of the definitions of indicators and its measurement. –Develop action plan Review the staffing (e.g., number of staff, roles and responsibilities) Strengthen staff capacity through training, coaching, supervision Ensure completeness of the filled data collection forms. Include M&E discussion in regular monthly meeting (e.g., record review and feedback, strengthen understanding of indicator definitions and required information, and etc.).

17 Thank you!


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