Quality assurance of routine data (4/10)

b) Routine data quality framework and existing routine data systems

Project/program activities are carried out and monitored at the delivery sites to quantify progress or efforts using a certain indicator.

According to the HMIS Facilitators Guide for Training of Trainers (Measure Evaluation) “an indicator is a variable that describes a given situation and thus permits measurement of changes over time. It transforms crude information into a form that is more suited for decision-making”.

The figure below provides schematic framework on how to evaluate routine data quality using 6 dimensions.

Schematic Framework of Data Quality
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Source: Measure Evaluation


Among existing routine data systems (click on the link at the bottom of the page for more details) certain seem to be better suited to the purpose of the national information platforms on nutrition: Health Management Information System (HMIS) – best suited, Integrated Diseases Surveillance and Response (IDSR), Sentinel Surveillance, and other Sector based data systems the less organised amongst all.

Sentinel surveillance data are also part of routine data. A sentinel surveillance system can be used to collect nutrition data. Unlike population-based surveillance, sentinel surveillance does offer greater design flexibility with participation requirements of various network partners.

A line ministry (such as health, agriculture, education) that implements nutrition-sensitive interventions will have its own data collection process and system. In many cases the HMIS is better organised and systematised than the information system of other sectors.

However, these routine data systems do not sufficiently integrate nutrition indicators yet. NIPN and other nutrition partners should advocate for integration of more nutrition indicators, both in short term information systems the sentinel surveillance systems during emergencies, but also in permanent, continuous information systems such as HMIS.

Existing routine data systems