Towards a Mobile Service Innovation Adoption Model for Health Workers in Private Health Providers in Uganda. Case Study: Marie Stopes Uganda
Year: 2016
Author: Muhebwa Cedric Anil
Supervisor: Sheba Nyakaisiki
Abstract
The African continent is seen as the world's second-largest and second most-populous continent, after Asia. It covers 6% of the earth’s total surface area and 22% of the total land area, with a population of approximately 1.6 billion people accounting for 16% of the world’s total population (World fact book, 2011). The rapid increase in mobile telephone use in sub Saharan Africa has generated concerns among researchers about possible ways in which this innovation can be leveraged to increase healthcare accessibility and efficiency. Over the years in Uganda, there have been numerous applications developed to facilitate healthcare service and access. However most of these have ended up at pilot phase and a few have been fully due improper alignment with the national e-health plans (Otto et al., 2015). The objective of the study was to investigate adoption and usage of mobile service innovations by health providers in the private health facilities in Uganda and then propose a model that can utilized to examine factors that affect adoption and usage.
The Case Study was Marie Stopes Uganda (BlueStar Healthcare Network) because it was listed among the biggest investors in mobile technology for health according to (AidLeap 2014). This was a cross sectional descriptive study. Respondents (n = 101) consisted of health workers derived through purposive sampling from 64 private health facilities in the study area. Questionnaires from 96 (100%) respondents were correctly filled and returned and 5 (100%) key informants interviewed. Data analysis reflected 96 respondents. Data was collected from the health workers using questionnaires. The collected data was analyzed quantitatively and qualitatively. Quantitative data was analyzed with the use of a simple frequency analysis (i.e. percentage). Inferential statistics were used. Qualitative data was analyzed by use of content analysis. Based on a number of acceptance models from the literature, a conceptual model was developed to analyze the arguments pertinent to a private health facility context. The most noticeable modification, compared to earlier models, is that social influence, technology service attributes and promotion play a role as external factors which affect the behavioral intentions of an individual by means of perceived usefulness (PU) and perceived ease of use (PEU) to actually use mobile technology.