Trauma Surveillance and Registry Development in Mozambique: Results of a 1‐Year Study and the First Phase of National Implementation
Bibliographic record
Abstract
BACKGROUND: Mozambique has had no policy-driven trauma system and no hospital-based trauma registries, and injury was not a public health priority. In other low-income countries, trauma system implementation and trauma registries have helped to reduce mortality from injury by up to 35%. In 2014, we introduced a trauma registry in four hospitals in Maputo serving 18,000 patients yearly. The project has since expanded nationally. This study summarizes the challenges, results, and lessons learned from this large national undertaking. METHODS: Between October 2014-September 2015, we implemented a trauma registry at four hospitals in Maputo. In October 2015, the project began to be expanded nationally. Physicians and allied health professionals at each hospital were trained to implement the registry, and each identified and trained data collectors. We conducted semi-structured interviews with the key stakeholders of this project to identify the challenges, results, and creative solutions implemented for the success of this project. RESULTS: Most participants identified the importance of having a trauma registry and its usefulness in identifying gaps in trauma care. The registry identified that less than 5% of injured patients arrived by ambulance, which served as evidence for the need for a prehospital system, which the Ministry of Health had already begun implementing. Participants also highlighted how the registry has allowed for a structured clinical approach to patients, ensuring that severely injured patients are identified early. Challenges reported included the high rates of missing data, the difficulty in establishing a streamlined flow of trauma patients within each hospital, and the bureaucratic challenges faced when attempting to improve capacity for trauma care at each hospital by introducing a trauma bay and new technologies. Participants identified the need to improve data completeness, to disseminate the results of the project nationally and internationally, to improve inter-divisional cooperation, and to continue educating health providers on the importance of registries. Participants also identified political instabilities in the region as a potential source of challenge in expanding the project nationally; they also identified the lack of uniform resource allocation and low personnel in many areas, especially rural, as a major burden that would need to be overcome. CONCLUSION: Introduction of a trauma registry system in Mozambique is feasible and necessary. Initial findings provide insight into the nature of traumas seen in Maputo hospitals, but also underscore future challenges, especially in minimizing missing data, utilizing data to develop evidence-based trauma prevention policies, and ensuring the sustainability of these efforts by ensuring continued governmental support, education, and resource allocation. Many of these measures are being undertaken.
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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 | 0.002 | 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".