Healthcare system’s preparedness to provide cardiovascular and diabetes-specific care in the context of geopolitical crises in Burkina Faso: a trend analysis from 2012 to 2018
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the trends of the availability and readiness of the healthcare system to provide cardiometabolic (cardiovascular diseases (CVD) and diabetes) services in Burkina Faso in multiple political and insecurity crises context. DESIGN: We performed a secondary analysis of repeated nationwide cross-sectional studies in Burkina Faso. DATA SOURCE: Four national health facility survey data (using WHO Service Availability and Readiness Assessment (SARA) tool) conducted between 2012 and 2018 were used. PARTICIPANTS: In 2012, 686 health facilities were surveyed, 766 in 2014, 677 in 2016 and 794 in 2018. PRIMARY AND SECONDARY OUTCOME MEASURES: The main outcomes were the availability and readiness services indicators defined according to the SARA manual. RESULTS: Between 2012 and 2018, the availability of CVD and diabetes services significantly increased (67.3% to 92.7% for CVD and 42.5% to 54.0% for diabetes). However, the mean readiness index of the healthcare system to manage CVD decreased from 26.8% to 24.1% (p for trend <0.001). This trend was observed mainly at the primary healthcare level (from 26.0% to 21.6%, p<0.001). For diabetes, the readiness index increased (from 35.4% to 41.1%, p for trend=0.07) during 2012-2018. However, during the crisis period (2014-2018), both CVD (27.9% to 24.1%, p<0.001) and diabetes (45.8% to 41.1%, p<0.001) service readiness decreased. At the subnational level, the readiness index for CVD significantly decreased in all regions but predominantly in the Sahel region, which is the main insecure region (from 32.2% to 22.6%, p<0.001). CONCLUSION: In this first monitoring study, we found a low level and decreased trend of readiness of the healthcare system for delivering cardiometabolic care, particularly during the crisis period and in conflicted regions. Policymakers should pay more attention to the impact of crises on the healthcare system to mitigate the rising burden of cardiometabolic diseases.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".