Socioeconomic inequalities in curative healthcare-seeking for children under five before and after the free healthcare initiative in Sierra Leone: analysis of population-based survey data
Bibliographic record
Abstract
BACKGROUND: Socioeconomic inequalities between and within countries lead to disparities in the use of health services. These disparities could lead to child mortality in children under 5 years by depriving them of healthcare. Therefore, initiatives to remove healthcare fees such as the Free Healthcare Initiative (FHCI) adopted in Sierra Leone can contribute to reducing these inequities in healthcare-seeking for children. This study aimed to assess the socioeconomic inequalities in healthcare-seeking for children under 5 years of age before and after the implementation of the FHCI. METHODS: Data were included on 1207, 2815, 1633, and 1476 children under 5 years of age with fever from the 2008, 2013, 2016, and 2019 nationwide surveys, respectively. Concentration curves were drawn for the period before (2008) and after (2013-2019) the implementation of the FHCI to assess socioeconomic inequalities in healthcare-seeking. Finally, Erreyger's corrected concentration indices were calculated to understand the magnitude of these inequalities. RESULTS: Before the implementation of the FHCI, there were inequalities in healthcare-seeking for children under five (Erreyger's corrected concentration index (CI) = 0.168, standard error (SE) = 0.049; p < 0.001) in favor of the wealthy households. These inequalities decreased after the implementation of the FHCI (CI = 0.061, SE = 0.033; p = 0.06 in 2013, CI = 0.039, SE = 0.04; p = 0.32 in 2016, and CI = - 0.0005, SE = 0.362; p = 0.98 in 2019). Furthermore, before the implementation of the FHCI, a significant pro-rich inequality in the districts of Kenema (CI = 0.117, SE = 0.168, p = 0.021), Kono (CI = 0.175, SE = 0.078, p = 0.028) and Western Area Urban (CI = 0.070, SE = 0.032, p = 0.031) has been observed. After the implementation of the FHCI in 2019, these disparities were reduced, 11 of the 14 districts had a CI around the value of equality, and only in 2 districts the pro-rich inequality were significant (Western Area Urban (CI = 0.035, SE = 0.016, p = 0.039) and Western Area Rural (CI = 0.066, SE = 0.030, p = 0.027)). CONCLUSION: The results of this study demonstrated that socio-economic inequalities in healthcare-seeking for children have been considerably reduced after the FHCI in Sierra Leone. To further reduce these inequalities, policy actions can focus on the increase of availability of health services in the districts where the healthcare-seeking remained pro-rich.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".