Evaluation of Diagnostic Imaging Capacity and the Role for Point-of-Care Ultrasound (POCUS) within the Zanzibar Health System
Bibliographic record
Abstract
Background: The Zanzibar Ministry of Health identified access to ultrasound (US) as a system priority due to limited diagnostic imaging capacity and consequent impact on patient care and requested a needs assessment in this regard. As a result, the objective of this study was to assess diagnostic imaging capacity focusing on ultrasound in Zanzibar, including health care providers’ (HCPs) current training, use, and barriers to implementation. Methods: A previously published ultrasound needs assessment survey was modified and administered on-site at the eight public hospitals in Zanzibar among a convenience sample of HCPs. Demographics, perceived US needs, current training and practice, and availability of specialty support were assessed. HCPs also completed focused personal interviews (FPIs) to explore experience with training, interests, and barriers to ultrasound. On-site diagnostic imaging modalities were assessed. Results: There were nine ultrasound machines present at six of the eight public hospitals assessed. All had x-ray, but only one had a CT scanner and a radiologist. There was no MRI capacity at the hospitals assessed at the time of the study. Survey data among 40 participants revealed that prior experience with POCUS was limited with only 10% reporting any prior ultrasound training or experience. The majority of those surveyed (72%), indicated a ‘high’ interest in learning ultrasound. Of those reporting interest in POCUS applications, obstetrics was the most often cited (70%). Lack of ultrasound machines (40%) and educators (28%) were identified as the greatest barriers. Conclusion: HCPs in Zanzibar have limited access to diagnostic imaging, including ultrasound, and expressed a high level of interest in learning point-of-care ultrasound. A shortage of machines and educators are the main barriers to widespread use. Obstetrics is the application for which ultrasound is currently most used and is the application HCPs are most interested in learning. Equipment and educational support for a POCUS program could improve care by increasing access to diagnostic imaging.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".