Revisiting Mhealth (Mobile Health) and Access to Care in Subsaharan Africa: Global, Regional and Individual Disparities
Improving access to care is an urgent agenda in sub-Saharan Africa (SSA). The needs for family planning services were met for 49.6% of population in Africa vs. 76.7% globally in 2016; antenatal care coverage for at least 4 visits was 54% in Africa vs. 64% globally in 2013. As an innovative solution to improving access to health services, mHealth or the use of mobile devices for medical and public health practice, has been widely acknowledged for its potential in the field of public health. ^ With growing enthusiasm on mHealth in SSA, this research attempted to give an answer to three questions on mHealth. First, what is policy readiness for mHealth of SSA countries compared at the global level? Second, what is the current distribution of mHealth programs in SSA? Third, what is the potential effectiveness of the mHealth program on family planning? ^ The answer to the first question was given in terms of policy readiness of mHealth at the global level. SSA had lower level of policy readiness compared to high income countries but globally, it was more likely to be at the advanced level. From the ordinal logistic regression analysis, 3 factors were associated with mHealth policy readiness - ICT development index (IDI), education for health professionals and the location in SSA. ^ In the second question, the current distribution of mHealth was evaluated at the regional level by using exploratory spatial data analysis to lay a groundwork for regional collaboration strategies. In SSA, the eastern region has comparative advantage for mHealth while some of the countries are left behind. South Sudan, Somalia and Rwanda were low-high outliers that have relatively little mHealth experience but are surrounded by those with much mHealth experience. Central African Republic is the low-low association with little mHealth experience for itself and its neighboring countries. ^ The third question investigated socioeconomic disparities and the effects of mHealth on family planning in Kenya by mixed effects logistic regression analysis. Older age, low levels of education and wealth, living in rural area and being married or living with a partner are important socioeconomic factors associated with disparities in mHealth experience for family planning. In the presence of socioeconomic disparities, future mHealth programs should aim for effective and equitable targeting. In evaluating the potential effects, mHealth experience for family planning was associated with contraceptive use/intention to use, implying the value of mHealth as an effective channel for family planning program.^
Lee, Seohyun, "Revisiting Mhealth (Mobile Health) and Access to Care in Subsaharan Africa: Global, Regional and Individual Disparities" (2017). Texas Medical Center Dissertations (via ProQuest). AAI10616999.