ArticleOxford open digital health2025
Experiences, challenges and lessons while implementing a clinical decision support system in Botswana.
Article in Oxford open digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Data warehousing in healthcare: enhancing resource allocation and decision-making in Botswana.Oxford open digital health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of information and communication technologies in healthcare has given rise to mobile health applications and services. For the developing world, mobile health has been hailed as being valuable for extending access to healthcare to underserved populations. More recently, mobile health applications support clinicians to quickly navigate decision making processes. An exemplar decision support system, VisualDx, was implemented in Botswana to provide reference materials at the point of care to support early diagnosis and management of complex dermatological conditions. This study shares experiences, challenges and lessons learnt while implementing VisualDx in Botswana. An explanatory sequential mixed methods feasibility study was conducted with 28 healthcare providers stationed at 20 clinics and hospital sites across Botswana. Nine recorded training sessions were conducted via Zoom and participants thereafter interacted with VisualDx on varying use cases. Quantitative and qualitative data were collected via surveys and a semi-structured interview per participant. Standard VisualDx App usage data was also collected. Descriptive statistics were generated and analyzed. Thematic analysis of interview transcripts was performed using Delve. Experiences, challenges and lessons learned throughout VisualDx implementation in Botswana cut across; Infrastructure, Data protection compliance, Image data quality, Continuous training support, artificial intelligence regulation, Participants' retention and Sustainable digital health funding. The implementation of VisualDx in Botswana illustrates both the value and the challenges of cross-sector and cross-border collaboration in driving adoption of eHealth tools. The lessons learned may inform future strategy for implementation of other eHealth platforms in Botswana and other similar developing countries.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.