Adoption of e-health for community monitoring of HIV/TB services and its predictors among staff of Non-Government Organisations in Kampala, Uganda

Introduction: The use of electronic data capture and digital health technologies can greatly improve patient healthcare outcomes, through augmenting diagnosis, prescription and treatment, and patient-centred care. The global strategy on digital health (2020-2025) by the World Health Organization promotes the use of eHealth as important for the achievement of health goals. However, adoption by Non-governmental organisations (NGO) staff meant to primarily use it to capture data is still sub-optimal. This study sought to assess the factors associated with eHealth adoption and use for community monitoring of HIV/TB services and its predictors among NGO staff in Kampala. Methods: A mixed-methods cross-sectional study was carried out among 110 staff who used eHealth in nine clinics from five NGOs providing HIV/TB services in Kampala. Interviewer-administered questionnaires were used to collect quantitative data. A key informant interview guide was used to collect qualitative data from 9 persons. Quantitative data were analysed using STATA version 14. Logistic regression was used to determine the factors associated with the adoption of eHealth at 95% CI. Qualitative data were analysed using a thematic analysis approach. Results: The respondents were predominantly female (60.9%), and the mean age was 33.6 years (SD=7.6). More than half of them were aged between 18 to 34 years (63.6 %). Slightly over half, 60/110 (54.5%) were in union, 46/110 (48.2%) were diploma holders, 34/110 (30.9%) had worked for their respective organisations for more than 5 years. Factors associated with eHealth use included data accuracy (AOR:0.04, 95% CI: 0.00-0.63) and interoperability (AOR: 0.26, 95% CI: 0.08-0.90). The AOR values were less than 1 indicating that lower perceived data accuracy and poor interoperability were barriers to eHealth adoption. This could be due to concerns about the reliability of digital records, challenges in integrating systems, or increased workload due to data inconsistencies. Other factors facilitating adoption and use included gender, readiness to use, user-friendliness, operation awareness, having features customised to HIV/TB data capture, training, real-time support and collegial support. Although female providers appeared more likely to adopt eHealth, this association was only suggestive and not statistically significant. Conclusion: eHealth adoption and use were influenced by a combination of interpersonal, technological, and external factors. Technological aspects such as data accuracy, interoperability, and system customization played a critical role in shaping user confidence and system efficiency. Interpersonal factors, including operational awareness and user-friendliness, affected individual willingness and capacity to engage with eHealth tools. Additionally, external enablers like training, real-time support, and broader organizational readiness facilitated adoption by improving competence and trust in the system. These findings highlight the need for a holistic approach to eHealth implementation, addressing both technical and human-centred challenges to ensure sustained adoption.