Updating a Rural Clinic in Tiburón, Haiti
Bibliographic record
Abstract
Background: Tiburón is a small fishing village in Haiti with a clinic overseen by the Oblate missionaries and the Ministry of Public Health and Population (MSPP). This village was hugely impacted by Hurricane Matthew in 2016, leading to increased health care demands. The clinic was inaccessible from the furthest parts of the village and lacked basic medication supplies and adequate manpower. We aimed to reinforce the infrastructure and update the clinic using a multifaceted approach. Methods: We developed a quality improvement project to strengthen the clinic's infrastructure and modernize its facilities with a comprehensive approach focused on enhancing health care for the people of Tiburón. We analyzed the data collected by MSPP statisticians, encompassing records of over 2000 patients visiting the clinic between 2017 and 2019. This analysis included all patients aged 1 to 80 years, with no exclusion criteria. We examined both pre- (before 2018) and post- (after 2018) intervention variables, including the number of patients, their gender, various visit types, and trends in encountered pathologies. In 2018, we implemented several interventions in collaboration with the MSPP, such as increasing staffing, expanding health care outreach efforts, providing financial support for medications, adopting a targeted approach to prevent common pathologies, educating and raising awareness about communicable and vaccine-preventable diseases, and placing greater emphasis on maternal health. Results: We assessed the effects of our interventions by comparing data from previous years using the quality metrics established by the MSPP. Significant changes were observed pre- and post-intervention, including an increase in the number of patients, a rise in all visit types, expanded health care outreach, a reduction in communicable and vaccine-preventable diseases, and improved maternal health. Conclusion: This was a promising quality improvement project, highlighting the improvement of studied variables after adding sustainable and efficient interventions. With our continued effort, we aim to facilitate future interventions based on the success of the current study to further update the clinic and to cater to the increasing health care needs of the population of Tiburón and other such underserved communities.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".