Status of radiological services in Addis Ababa public hospitals.
Bibliographic record
Abstract
BACKGROUND: The availability and quality of radiological service in the developing countries are generally poor. Ethiopia is one of the countries where overall health service has been compromised by inadequate & poorly maintained infrastructure and scarcity of health professionals. Radiological service is a resource intensive unit in a hospital and most developing countries radiological service is expected to be poor or may not be available at all. However, there is no study conducted to assess the radiological service in Ethiopia. OBJECTIVE: The aim of the study is to assess the status of radiological service in all public hospitals in Addis Ababa, capital of Ethiopia, and to render insight to the overall national service status. METHODS: A cross sectional survey was conducted from Aug 2008 to Oct 2009 G C in all twelve public hospitals in Addis Ababa, including specialized and military hospitals. Self administered pre-tested questioners were used to collect data from key informants, chief radiographers and radiologist. In addition, departmental daily work record book was used to extract the type of radiological examination performed Data analysis was done manually. RESULT: All hospitals in the study provide a basic level of radiological services. Plain x-ray and ultrasound is the type of service (100%) available, whereas services like mammography (9%), CT scan (18%) and MRI (0%) were found to be the least available. There are a total of 78 radiographers and 20 radiologists in Addis Ababa public hospitals with no radiologist in three. The average number of examinations performed in a year amounts to 113,204 and US and routine x-ray examinations account for nearly 98% of the service offered The study showed 25% of the radiological equipments are non-functional and no appropriately trained dark room technicians & no maintenance staffpresent in all hospitals CONCLUSION AND RECOMMENDATION: This study verifies the poor radiological infrastructure, poor level of support and the basic nature of the radiological service in the capital. We believe this finding can be used as an indirect indicator of the possible worse scenario in the regional and peripheral hospitals. Therefore a nation- wide survey & plannedgovernment intervention is recommended to improve the radiological service.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".