Training Curriculum for the Integrated Approach to Family Planning Data Quality Assessment

Guidelines
Curriculum

Data for Impact (D4I), funded by the United States Agency for International Development (USAID), and the Track20 project funded by the Bill & Melinda Gates Foundation, are projects that focus on improving health management information systems (HMIS) data quality and use. These guidelines represent their joint effort to target data quality in a way that accounts for limited resources in family planning (FP) programs by providing a framework to integrate two tools–MEASURE Evaluation’s Routine Data Quality Assessment (RDQA) tool and Track 20’s Service Statistics to Estimated Modern Use (SS to EMU) tool–specifically developed for HMIS data quality and use through a top-down and bottom-up approach.

Combining the RDQA approach with the SS to EMU approach for identifying sources of “quality data issues” in data represents an important step toward improving targeting data management and quality analysis and moving these approaches to facilities and subnational levels with the greatest need. This training collection includes a curriculum document, a guidance document, and 13 PowerPoint presentations to provide guidance on how to use the SS to EMU and RDQA integrated approach to assess and monitor FP data quality performance.

Access the Training Curriculum for the Integrated Approach to Family Planning Data Quality Assessment (French) and User Guidelines for the Integrated Approach to Family Planning Data Quality Assessment (French).

Download the curriculum presentations:

  1. Introduction to FP Data Quality (French)
  2. Data Quality Conceptual Framework and Dimensions (French)
  3. FP Data Quality Problems (French)
  4. Data Quality Assessment Methods (French)
  5. Introduction to Service Statistics to Estimated Modern Use Tool (French)
  6. SS to EMU Data Entry (French)
  7. SS to EMU Output Review (French)
  8. SS to EMU Final Output Review (French 1, French 2, French 3,)
  9. Introduction to RDQA (French)
  10. Identification and Selection of Indicators for Data Quality Verification (French)
  11. Selection of Sites for Data Quality Verification (French)
  12. Site Data Verification (French)
  13. Data Quality Analysis and Development of a Plan of Action (French)

Download a zip file containing the full collection (French).