Data Validation with DHIS Software

1. Data Validation with DHIS Software By Zufan Abera

2. Outline • Objectives • Rationale • Validation • Data Validation • Validation operators • Flow chart • Summary

3. Objective of the session • To Enable Health Managers to Validate their data using DHIS software

4. Rationale • Data quality is very important for building effective HIS • Data quality is a problem in the health care settings • There is a need to improve data Quality

5. Validation • The process of checking if something satisfies a certain criterion • Check if solution or process is correct • Suited for its intended use. • Validation can be used in different fields.

6. Validation cont. • Examples • Declare or make legally valid of documents • Effectiveness and Reproducibility of the process to produce a medical product • Total OPD attendants should > Malaria cases

7. Data Validation • Checking that data inserted into an application satisfies pre-determined formats • One way of picking up errors of data • Verify correct data can be entered into a database. • Check routines or data for • meaningfulness • Usefulness • Can be done in application software, such as DHIS

8. Data Validation cont. • District Health Information Software (DHIS) has a functionality for checking data validity • Before you do validation • Validation rule must be already defined • The validation rules are set based on comparison of two or more data elements • We use the following operators

9. Validation operators • Operators are functions in mathematics that use for comparison • Types of validation operators include • Equal to = • Less than < • Greater than >

10. Validation operators cont. • There must be at least two data elements or values to make comparison • One on the right side and one on the left side • Example

11. Out come of validation • Validation passed successfully • Validation violation

12. Starting point for data validation

13. Steps to follow

14. Exercise • Validate the Immunization data of lP Diana clinic for January 2009 • Use the guideline and examples provided

15. Any Question

16. Summary • Validation is one way of checking the data Quality • It can be done using different application software, eg. DHIS • You are expected to take action based on the validation out come

17. Summary cont.

18. Summary cont.

19. Summary cont. • What actions can be taken when the you get • Violation of validation • Validation pass successfully