A Locally Developed Electronic Health Platform in Uganda: Development and Implementation of Stre@mline
Bibliographic record
Abstract
BACKGROUND: Electronic health records (EHRs) are especially important in low-resource settings due to their potential to address unique challenges such as a high number of patients requiring long-term treatments who are lost to follow-up, the frequent shortages of essential drugs, poor maintenance and storage of records, and inefficient clinical triaging. However, there is a lack of affordable and practical EHR solutions. Stre@mline is an EHR platform that has been locally developed by Ugandan clinicians and engineers in Southwestern Uganda. It is tailored to the specific context and needs of low-resource hospitals. It operates without internet access, incorporates locally relevant standards and key patient safety features, has a medication inventory management component, has local technical support available, and is economically sustainable without funding from international donors. Stre@mline is currently used by over 60,000 patients at 2 hospitals, with plans to expand across Uganda. OBJECTIVE: The purpose of this article is to describe the key opportunities and challenges in EHR development in sub-Saharan Africa and to summarize the development and implementation of a "Made-for-Africa" EHR, Stre@mline, and how it has led to improved care for over 60,000 vulnerable patients in a rural region of Southwestern Uganda. METHODS: A quantitative user survey consisting of a set of 33 questions on usability and performance was conducted at Kisiizi Hospital. Users responded to each question through a Likert scale with the values of strongly disagree, disagree, agree, and strongly agree. Through purposive sampling, 30 users were identified and 28 users completed the survey. RESULTS: We found that users were generally very satisfied with the ease of use of Stre@mline, with 96% (27/28) finding it easy to learn and 100% (28/28) finding it easy to use. Users found that Stre@mline was helpful in improving both clinical efficiency and enhancing patient care. CONCLUSIONS: The partnership of local clinicians and developers is crucial to the design and adoption of user-centered technologies tailored to the specific needs of low-resource settings. The EHR described here could serve as a model for the development of future technologies suitable for developing countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".