Primary Care Provision by Volunteer Medical Brigades in Honduras: A Health Record Review of More Than 2,500 Patients Over Three Years
Bibliographic record
Abstract
The weak health system in Honduras contributes to poor health indicators. To improve population health, a number of volunteer medical brigades from developed countries provide health services in Honduras. To date, there is little information on the brigades' activities and impact. The primary objective of this article is to increase understanding of the type of health care provided by voluntary medical brigades by evaluating and presenting data on patients' presenting symptoms, diagnoses, and care outcomes. The article focuses on an ongoing medical brigade organized by Canadian health professionals in conjunction with Honduras' largest national non-governmental organization. This is a descriptive study of data that are routinely collected by volunteer Canadian health care professionals. Data on all patients presenting to temporary primary health care facilities across Honduras between 2006 and 2009 were analyzed. The data were used to analyze patient demographics, presenting symptoms, diagnoses, and treatments. We found that the brigades provide additional human resources to the relatively weak Honduran health care system. However, while brigades may increase solidarity between Hondurans and Canadians, concerns persist regarding cost-effectiveness and continuity of care for conditions treated by short-term brigade volunteers. Greater scrutiny is needed to increase brigades' effectiveness and ensure they are supportive of domestic health systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".