Module Four : Home

In conducting analyses of MCH data for decision-making or evaluation purposes, data quality is of prime importance. Poor attention to data quality could lead to erroneous conclusions as well as inappropriate policy and programmatic recommendations. This module will focus upon data quality issues in MCH data analysis, using examples drawn from a variety of datasets.

Through completion of this module, students will be to learn:

1. Describe three dimensions of data quality.
2. Ascertain data completeness and its correlations.
3. Describe three strategies for addressing data quality problems.
4. Discuss the special cases of fetal death and unintended pregnancy ascertainment of non-response.
5. Conduct a sensitivity analysis to examine the best/worst case scenario of the impact of non-response.