Version 1
: Received: 24 August 2021 / Approved: 25 August 2021 / Online: 25 August 2021 (10:51:48 CEST)
How to cite:
Namatovu, H.K.; Semwanga, A.R. Barriers and Facilitators of eHealth Adoption among Patients in Uganda – A Quantitative Study. Preprints2021, 2021080487. https://doi.org/10.20944/preprints202108.0487.v1
Namatovu, H.K.; Semwanga, A.R. Barriers and Facilitators of eHealth Adoption among Patients in Uganda – A Quantitative Study. Preprints 2021, 2021080487. https://doi.org/10.20944/preprints202108.0487.v1
Namatovu, H.K.; Semwanga, A.R. Barriers and Facilitators of eHealth Adoption among Patients in Uganda – A Quantitative Study. Preprints2021, 2021080487. https://doi.org/10.20944/preprints202108.0487.v1
APA Style
Namatovu, H.K., & Semwanga, A.R. (2021). Barriers and Facilitators of eHealth Adoption among Patients in Uganda – A Quantitative Study. Preprints. https://doi.org/10.20944/preprints202108.0487.v1
Chicago/Turabian Style
Namatovu, H.K. and Agnes Rwashana Semwanga. 2021 "Barriers and Facilitators of eHealth Adoption among Patients in Uganda – A Quantitative Study" Preprints. https://doi.org/10.20944/preprints202108.0487.v1
Abstract
The adoption of eHealth has not made great strides in Uganda especially among patients despite its potential in improving patient outcomes through access to care, patient engagement and its ability to reduce unnecessary hospital visits. Previous studies have focused on barriers and facilitators of eHealth in general. None has examined the adoption of eHealth among patients. Therefore, this study set out to investigate the barriers and facilitators of eHealth adoption among patients in Uganda. A cross-sectional survey was conducted in four districts across the country. A total of 292 patients of 18 years and above participated in the study and their selection was through simple random sampling. The bivariate analysis results revealed that education level (χ2 = 14.9, ρ<0.05), gender (χ2 = 4.95, ρ<0.05) and location (χ2 = 85.9, ρ<0.05) have a statistical significant relationship with eHealth adoption. The logistic regression model further revealed that male patients (OR=2.662), those with master’s degree and above (OR=2.2797) and those residing in Kampala (OR=.012) were more likely to use eHealth systems than their counterparts. The success of eHealth requires players in the health sector to ardently focus on the socio-demographic factors of the users, technological and hospital conditions if eHealth adoption is to ensue.
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
