Effects of Demographic Characteristics on the Electronic Health Management Information System (eHMIS) Functions in Tanzania

Abstract

We assessed the use of Electronic Health Management Information – eHMIS – and the influence of demographic characteristics on the eHMIS functions. In particular, we explore changes in the usage of eHMIS among health workers. We also determined the effects of demographic characteristics on the usage of eHMIS and assessed any improvement in the ability to use eHMIS after its development. A mixed research design approach was adopted. The respondents were the clinical and non-clinical staff. Data was collected using interviews and questionnaires in three phases: baseline, midline, and final survey. The findings revealed an increase in the frequency of use of the eHMIS for entering and searching data entry from the midline to the final review. Apart from entering data, browsing, and retrieving previously recorded data, other eHMIS functions were not affected by demographic characteristics. On self-efficacy, there was an increase in health workers who felt comfortable using the system in the final survey compared to the baseline survey. In conclusion, enough training, user experience, and support from the management are very important in effective eHMIS mplementation. performs calculations, supports decision making, attaining competitive advantage, better management of diseases, increases productivity, stimulates research and information dissemination in different formats (Namakula & Kituyi, 2014; Winter et al., 2010). WHO states that an eHMIS is among the six components of a health system that produces, analyses, and disseminates timely and reliable health information on health status, determinants and systems performance (World Health Organization, 2007). eHMIS constitutes modules that deal with health management information reporting, finance, administration operations, and drugs inventory management (Amin et al., 2011; Ismail et al., 2013). For many years, several countries have devoted significant funds to improving eHMIS (Amin et al., 2011; Ismail et al., 2013; Littlejohns et al., 2003; Mahundi et al., 2018; Wilms et al., 2014). Despite all their efforts, it has not been easy to integrate eHMIS to fully operate in health facilities. In Tanzania, the early version of eHMIS known as Mfumo wa Taarifa za Uendeshaji wa Huduma za Afya (MTUHA), had challenges such as data inconsistencies, data duplication, and other parallel information systems (Nyamtema, 2010; Wilms et al., 2014).