Primary health care contribution to improve health outcomes in Bogota-Colombia: a longitudinal ecological analysis
Bibliographic record
Abstract
BACKGROUND: Colombia has a highly segmented and fragmented national health system that contributes to inequitable health outcomes. In 2004 the district government of Bogota initiated a Primary Health Care (PHC) strategy to improve health care access and population health status. This study aims to analyse the contribution of the PHC strategy to the improvement of health outcomes controlling for socioeconomic variables. METHODS: A longitudinal ecological analysis using data from secondary sources was carried out. The analysis used data from 2003 and 2007 (one year before and 3 years after the PHC implementation). A Primary Health Care Index (PHCI) of coverage intensity was constructed. According to the PHCI, localities were classified into two groups: high and low coverage. A multivariate analysis using a Poisson regression model for each year separately and a Panel Poisson regression model to assess changes between the groups over the years was developed. Dependent variables were infant mortality rate, under-5 mortality rate, infant mortality rate due to acute diarrheal disease and pneumonia, prevalence of acute malnutrition, vaccination coverage for diphtheria, pertussis, tetanus (DPT) and prevalence of exclusive breastfeeding. The independent variable was the PHCI. Control variables were sewerage coverage, health system insurance coverage and quality of life index. RESULTS: The high PHCI localities as compared with the low PHCI localities showed significant risk reductions of under-5 mortality (13.8%) and infant mortality due to pneumonia (37.5%) between 2003 and 2007. The probability of being vaccinated for DPT also showed a significant increase of 4.9%. The risk of infant mortality and of acute malnutrition in children under-5 years was lesser in the high coverage group than in the low one; however relative changes were not statistically significant. CONCLUSIONS: Despite the adverse contextual conditions and the limitations imposed by the Colombian health system itself, Bogota's initiative of a PHC strategy has successfully contributed to the improvement of some health outcomes.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".