Impact of Waiving Out-of-Pocket Access Fees on HIV Testing and Linkage Services in Rivers State, Nigeria
Bibliographic record
Abstract
Introduction: The financial implications of accessing health services negatively impact end-users and result in the non-utilization of healthcare services in most resource-poor countries. Direct and indirect costs of access to HIV services impede the uptake and adherence to ART, thereby hindering viral suppression in these regions. Evidence showed that out-of-pocket user fee waivers effectively improve access to healthcare services and expand their utilization. The payment of out-of-pocket user fees to access HIV services in Rivers State affected linkage to ART and was consequently waived to increase uptake of HIV services. The study aimed to determine the waiver's impact on linkage to ART.
 Methods: descriptive trend study to determine the difference in linkage to ART services following the waiver of access fees using data collected from the HIV control program, Rivers State.
 Findings: There was a gradual increase in the Number of individuals who received HIV Testing Services (HTS) and received their test results (HTS_TST_POS) after the implementation of the user fee waiver, the total HTS_TST_POS during the study period was 157,525; with a mean (IQR) of 1101.57 (107, 2061) HTS_TST_POS per week. The increase occurred between the third quarter of 2019 and the second quarter of 2021, after which a decline occurred. The waiver of the out-of-pocket payments policy was announced about week 8 of 2021, after which linkage to ART consistently tethered above 90%. The weekly mean (IQR) value of linkage to ART was 98.7% (76.6%, 105.9%); and ranged between 94% to 100% within yearly quarters; there was a 100% linkage to ART throughout the year 2021. The total number of persons currently on treatment increased from 21,914 to 173,212.
 Conclusion: Although the evidence supporting the effectiveness of user fee waiver as an intervention is debatable, removing out-of-pocket payments to access HIV services was effective in Rivers State and significantly improved linkage to ART.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".