Data Validation with DHIS Software By Zufan Abera.

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Presentation transcript:

Data Validation with DHIS Software By Zufan Abera

Outline Objectives Rationale Validation Data Validation Validation operators Flow chart Summary

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

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

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.

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

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

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

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

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

Out come of validation Validation passed successfully Validation violation

Starting point for data validation

Steps to follow

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

Any Question

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

Summary cont.

What actions can be taken when the you get – Violation of validation – Validation pass successfully