
Research Article
Barriers and Facilitators of eHealth Adoption Among Healthcare Providers in Uganda – A Quantitative Study
@INPROCEEDINGS{10.1007/978-3-031-06374-9_15, author={Hasifah K. Namatovu and Agnes R. Semwanga and Vincent M. Kiberu and Livingstone Ndigezza and Mark A. Magumba and Swaib K. Kyanda}, title={Barriers and Facilitators of eHealth Adoption Among Healthcare Providers in Uganda -- A Quantitative Study}, proceedings={e-Infrastructure and e-Services for Developing Countries. 13th EAI International Conference, AFRICOMM 2021, Zanzibar, Tanzania, December 1-3, 2021, Proceedings}, proceedings_a={AFRICOMM}, year={2022}, month={5}, keywords={eHealth Healthcare providers Barriers Facilitators Adoption}, doi={10.1007/978-3-031-06374-9_15} }
- Hasifah K. Namatovu
Agnes R. Semwanga
Vincent M. Kiberu
Livingstone Ndigezza
Mark A. Magumba
Swaib K. Kyanda
Year: 2022
Barriers and Facilitators of eHealth Adoption Among Healthcare Providers in Uganda – A Quantitative Study
AFRICOMM
Springer
DOI: 10.1007/978-3-031-06374-9_15
Abstract
Adoption of eHealth among healthcare providers in Uganda is still facing numerous challenges despite several studies indicating the potential of digital health systems in improving health outcomes. Therefore, this study set out to investigate the barriers and facilitators of eHealth adoption among healthcare providers in Uganda. A cross-sectional study using a quantitative approach was used to collect data from 216 healthcare providers working in 78 health facilities covering a period of October 2020 – March 2021. Analysis was done using Pearson’s Chi-square and descriptive statistics. Main findings indicated that 59% of the respondents had never used any eHealth system prior to the study. The regional distribution of eHealth uptake showed that Kampala had the highest users 61 (69%) while Gulu had the least 4 (5%). Employing a .05 criterion of statistical significance, the findings reveal that eHealth adoption and education level (χ2 = 40.72, ρ < 0.05), age (χ2 = 13.08, ρ < 0.05), location (χ2 = 20.96, ρ < 0.05), gender (χ2 = 4.40, ρ < 0.05) and institutional place of work (χ2 = 49.67, ρ < 0.05) are statistically significant. Furthermore, training users, ease of use, usefulness of the system and communicating eHealth benefits (µ = 4.15 ± .758, µ = 4.05 ± .888, µ = 3.76 ± .836, µ = 3.93 ± .827) had the highest mean contribution as facilitators of eHealth adoption, respectively. Any policy that targets integration of eHealth should take into account the demographic characteristics of health professionals, while paying attention to the organizational and technological factors. Future research should investigate eHealth adoption in patients and hospital administrators.