Cost-effectiveness of increased contraceptive coverage using family planning benefits cards compared with the standard of care for young women in Uganda
Bibliographic record
Abstract
BACKGROUND: Uganda has a high population growth rate of 3%, partly due to limited access to and low usage of contraception. This study assessed the cost-effectiveness of the family planning benefits cards (FPBC) program compared to standard of care (SOC). The FPBC program was initiated to increase access to modern contraception among young women in slums in Kampala, Uganda. METHODS: We developed a decision-analytic model (decision tree) and parameterized it using primary intervention data together with previously published data. In the base case, a sexually active woman from an urban slum, aged 18 to 30 years, was modelled over a one-year time horizon from both the modified societal and provider perspectives. The main model outcomes included the probability of unintended conception, costs, and incremental cost-effectiveness ratio (ICER) in terms of cost per unwanted pregnancy averted. Both deterministic and probabilistic sensitivity analyses were conducted to assess the robustness of the modelling results. All costs were reported in 2022 US dollars, and analyses were conducted in Microsoft Excel. RESULTS: In the base case analysis, the FPBC was superior to the SOC in outcomes. The probability of conception was lower in the FPBC than in the SOC (0.20 vs. 0.44). The average societal and provider costs were higher in the FPBC than in the SOC, i.e., $195 vs. $164 and $193 vs. $163, respectively. The ICER comparing the FPBC to the SOC was $125 per percentage reduction in the probability of unwanted conception from the societal perspective and $121 from the provider perspective. The results were robust to sensitivity analyses. CONCLUSION: Given Uganda's GDP per capita of $1046 in 2022, the FPBC is highly cost-effective compared to the SOC in reducing unintended pregnancies among young women in low-income settings. It can even get cheaper in the long run due to the low marginal costs of deploying additional FPBCs. TRIAL REGISTRATION: MUREC1/7 No. 10/05-17. Registered on July 19, 2017.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".