The health management Information system in Malawi

Information on available resource- and service production for the health sector is crucial for any government in order to manage it well. Collecting information of high quality on the health sector has however proven to be a challenging task.

This report is an assessment of data from the Health Management Information Systems (HMIS) in Malawi and suggests a way to improve data quality. The assessment is based on a “desk study” of the Malawian HMIS data. A statistical approach to improve data quality is presented, and it is used to identify possible data errors reported by the health facilities. Among other, the goal is to show a method for prioritizing the use of limited editing resources where they can improve quality the most.

This quality assessment of the Malawian HMIS data has 4 objectives:

 1. Identify areas for initial improvement of data quality

2. Present general guidelines for data editing

3. Present use of statistical methods to improve data quality

4. Recommend future activity

This quality assessment is from 2014/2015 (desk study) and focuses on reported Malawian HMIS data for 2013, but for some analysis 2012 data is also included.

Missing information is a severe threat to the Malawian HMIS data. A first step should be to reduce the amount of missing information. Further, it is also recommended to prioritize identifying health facilities that have errors influencing the end result at aggregated level.

Improving quality by analysing already collected data to point out weaknesses in the data is an efficient approach. By doing this, a highly recommended process of working in a “circular” manner to improve quality will be established.

The Health Information Systems Programme (HISP) is a global network emerging from the Department of Informatics at the University of Oslo. HISP has developed the District Health Information system (DHIS), a free open source software specialized for HMIS. Today HMIS data in Malawi is collected using DHIS2. The methods for editing suggested in this report can be implemented in DHIS2.

The aim of the suggested approach for improving data quality is to: Avoid missing data from health facilities, correct major errors and improve the source.