Willingness to pay for Social Health Insurance and associated factors among Public Civil Servants in Ethiopia: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The provision of equitable and accessible healthcare is one of the goals of universal health coverage. However, due to high out-of-pocket payments, people in the world lack sufficient health services, especially in developing countries. Thus, many low and middle-income countries introduced different prepayment mechanisms to reduce large out-of-pocket payments and overcome financial barriers to accessing health care. Though many studies were conducted on willingness to pay for social health insurance in Ethiopia, there is no aggregated data at the national level. Therefore, this systematic review and meta-analysis aimed to estimate the pooled magnitude of willingness to pay for social health insurance and its associated factors among public servants in Ethiopia. METHOD: Studies conducted before June 1, 2022, were retrieved from electronic databases (PubMed/Medline, Science Direct, African Journals Online, Google Scholar, and Web of Science) as well as from Universities' digital repositories. Data were extracted using a data extraction format prepared in Microsoft Excel and the analysis was performed using STATA 16 statistical software. The quality of the included studies was assessed using the Newcastle-Ottawa Scale for cross-sectional studies. To evaluate publication bias, a funnel plot, and Egger's regression test were utilized. The study's heterogeneity was determined using Cochrane Q test statistics and the I2 test. To determine the pooled effect size, odds ratio, and 95% confidence intervals across studies, the DerSimonian and Laird random-effects model was used. Subgroup analysis was conducted by region, sample size, and publication year. The influence of a single study on the whole estimate was determined via sensitivity analysis. RESULT: To estimate the pooled magnitude of willingness to pay for the Social Health insurance scheme in Ethiopia, twenty articles with a total of 8744 participants were included in the review. The pooled magnitude of willingness to pay for Social Health Insurance in Ethiopia was 49.62% (95% CI: 36.41-62.82). Monthly salary (OR = 6.52; 95% CI:3.67,11.58), having the degree and above educational status (OR = 5.52; 95%CI:4.42,7.17), large family size(OR = 3.69; 95% CI:1.10,12.36), having the difficulty of paying the bill(OR = 3.24; 95%CI: 1.51, 6.96), good quality of services(OR = 4.20; 95%CI:1.97, 8.95), having favourable attitude (OR = 5.28; 95%CI:1.45, 19.18) and awareness of social health insurance scheme (OR = 3.09;95% CI:2.12,4.48) were statistically associated with willingness to pay for Social health insurance scheme. CONCLUSIONS: In this review, the magnitude of willingness to pay for Social Health insurance was low among public Civil servants in Ethiopia. Willingness to pay for Social Health Insurance was significantly associated with monthly salary, educational status, family size, the difficulty of paying medical bills, quality of healthcare services, awareness, and attitude towards the Social Health Insurance program. Hence, it's recommended to conduct awareness creation through on-the-job training about Social Health Insurance benefit packages and principles to improve the willingness to pay among public servants.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".