WHO Data Quality Assessment Tools: Ensuring Reliable Health Information
Sound decisions are based on sound data. Meaningful analysis of health facility data requires insights into the quality of the data; yet the quality of Routine Health Information Systems (RHIS) data is an ongoing challenge in many contexts. It is therefore essential to ensure that facility data are of good quality.
To address these challenges, the World Health Organization (WHO) has developed a suite of Data Quality Assessment (DQA) tools aimed at supporting countries in assessing and improving the quality of RHIS data. These tools provide a standardized and holistic approach to data quality, promoting the institutionalization of routine data quality assessment.
The Data Quality Review (DQR) Toolkit
The Data Quality Review (DQR) toolkit proposes an integrated approach to data quality. The DQR framework and toolkit is meant to support routine annual and periodic, independent assessments of facility-reported data. This document lays out the overarching framework of the DQR and introduces the methodology, metrics and different components of the toolkit. It unifies and builds upon previous tools and methods designed to assess data quality at facility level, taking into account best practices and lessons learned from many countries.
The DQR toolkit offers a multi-pronged approach that ensures a comprehensive and holistic review of health facility data quality. The DQR toolkit includes guidelines and tools that lay the basis for a standardized and holistic approach to data quality that promotes institutionalization of routine data quality assessment in countries.
For countries that do not use DHIS2, Excel and CSPro tools are available together with training materials.
WHO Data Quality Assurance (DQA) Toolkit
WHO has produced the Data Quality Assurance (DQA) toolkit to support countries in assessing and improving the quality of RHIS data. The DQA toolkit includes an application for use in the DHIS2 for routine data quality checks and for annual data quality desk review. New data quality assurance resources targeting district-level users are currently pending publication.
WHO Data Quality Report Card (DQRC)
The desk review component of the DQRC can be done using the WHO Data Quality Assessment (DQA) Tool, an Excel-based tool that compares health facility records against health information system reported data.
WHO's Data Quality Report Card (DQRC) examines the quality of data generated by a health facility-based information system for four core tracer indicators: antenatal care first visit, health facility deliveries, diphtheria-pertussis-tetanus third dose, and outpatient department visits. The tool quantifies problems of data completeness, accuracy, and external consistency, and provides valuable information on fit-for-purpose of health facility data to support planning and annual monitoring.
Routine Data Quality Assessment (RDQA)
The Routine Data Quality Assessment (RDQA) is a simplified, self-assessment version of the DQA Tool. It allows programs and projects to assess the quality of their own data and strengthen their data management and reporting systems. The RDQA is generic with regard to indicators and programs.
It is intended for use with or without rigorous sampling methods. It is designed by and for staff collecting and using immunization data at national, provincial or district levels. as highlighted in the Reaching Every District (RED) approach
The DQS aims to determine :
- the accuracy of reported figures for coverage (i.e. number of immunizations) and for any other immunization system indicator
- the quality of any component of the immunization monitoring system
The assessment includes a review of data accuracy at different levels and a self-designed questionnaire reviewing monitoring quality issues (e.g.
A Menu of Tools for Data Quality Assessment and Review
Robust systems are essential to track progress toward health objectives, such as the United Nations Sustainable Development Goals, and to support evidence-based decision making. This document presents a menu of options for data quality assessment and is meant to provide guidance on which approach would be the most suitable for the data and system to be assessed. The scope of the assessment and the depth of data to be collected will depend on the purpose of the assessment.
