Applying the Activity Theory and the User Centered Design Framework to Develop a Web-Based Health Indicator Management Tool Case Study: Applying Science to Strengthen and Improve Systems (Assist) Project
Author: Musenge Kenneth
Supervisor: Richard Ssembatya
In most developing countries, particularly in sub-Saharan Africa, health indicators data collection, processing, reporting and storage has been dominated by paper-based approach at times generating incomplete and inaccurate reports. Evidence from literature shows that the continued use of paper-based systems contributes to poor data quality in terms of reliability, availability, timeliness, completeness and this compromises health service delivery. In Malawi, for instance it was found that the use of paper-based health facility reports to generate national summaries resulted in a twelve percent underreporting of persons on first-line antiretroviral treatment because many sites did not submit accurate data to the national level. In South Africa, It was found that 2.5% of the total data values that should have been collected at 10 primary health care clinics using a paper-based system were missing while 25% of the data were outside the minimum and maximum values specified for the facilities. A conception inquiry at a USAID funded project in Uganda also revealed similar problem.
This project addressed the above problems by developing a Web based Health Indicators Management tool that employed the Activity Theory and the User Centered Design (UCD) approach. Employing the Activity theory and the UCD approach ensured that users and the way they interacted with the system was of prime focus. The synergic result was a solution that provides usability measures for the Ugandan local context in terms of effectiveness, efficiency and satisfaction of managing and monitoring health indicators. The solution is anticipated to cause minimal disruptions to workflow since participants were heavily involved and learnt a lot during the process. This is expected to minimize interruptions in productivity that may be a result of learning a new system. It is anticipated that the solution will benefit USAID ASSIST by drastically improving the processing, management and control of health indicators.