JMIR Publications

ABSTRACT

Background:

Botswana, like many developing countries, has identified eHealth as a means of improving healthcare service provision and delivery. The National Malaria Programme (NMP) in Botswana has implemented the District Health Information System version 2 (DHIS2) to support timely Malaria case reporting across its 27 health districts. Despite the potential benefits of the DHIS2 platform towards improving Malaria case-based surveillance in Botswana, it must be noted that implementation of any eHealth system is never without challenges. Barriers to the implementation of eHealth innovations within the healthcare setting may arise at the individual or organizational levels. As such, evaluating perceptions of the intended users about the technology is an important step that could inform the sustainable implementation of eHealth systems. Nonetheless, the implementation of DHIS2 for Malaria case-based surveillance in Botswana was undertaken without prior user perception evaluation, living the Botswana Ministry of Health and Wellness with uncertainty regarding the likely or unlikely acceptance and use of the DHIS2. Hence this study employed the Technology Acceptance Model (TAM) to understand the DHIS2 user perceptions and potential issues around the system acceptance and usability.

Objective:

This study used TAM to evaluate the user acceptance of the DHIS2 platform for Malaria case-based surveillance in Botswana.

Methods:

The study approach, as well as the data collection, were informed by constructs underlying the TAM. Survey and focus group discussions were undertaken with 32 participants (27 DHIS2 core users across 27 health districts and five Malaria Program personnel at the Ministry of Health).

Results:

Overall, positive responses across all TAM constructs were recorded. However, participants also noted some organizational-related issues that could compromise user acceptance of the DHIS2 platform.

Conclusions:

According to TAM, participants’ responses indicate their acceptance of DHIS2 platform. However other models used to predict technology adoption and based on varying theories also exist. As such based on the findings from this study alone, we cannot conclusively predict successful adoption of DHIS2 towards Malaria case-based surveillance in Botswana. The authors propose organizational readiness as a better predictor of technology adoption. Clinical Trial: NA.