ArticleFrontiers in public health2025
Patterns of claims and determinants of claim rejections in Kuwait's National Health Insurance for Retirees (AFYA): a comprehensive analysis.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Health insurance claim rejections can impose significant administrative and financial burdens, yet data from emerging national programs are limited. Kuwait's AFYA program, launched in 2016 for retirees, provides a valuable opportunity to study rejection patterns and identify the demographic and service-level factors that influence denial rates in a rapidly evolving high-income context. Methods: This retrospective study analyzed 4.44 million AFYA claims from 2016 to 2023. Key variables included beneficiary characteristics (age group, sex), provider type, service category (dental, medical, pharmaceutical), claimed amount, and claim year. Logistic regression was employed to determine predictors of claim rejection, controlling for all the above factors. Sensitivity analyses excluded the top 1% of claimed amounts to check for robustness. Results: The overall rejection rate was 3.85%, lower than reported rates in some established systems. Younger retirees (under 40) had 1.82 times higher odds of claim denial than the reference group (56-60), and female beneficiaries had 1.21 times higher odds than males. Dental services were associated with a 2.28-fold increase in rejections relative to pharmaceutical claims. Laboratory claims, though relatively rare, showed exceptionally high rejection proportions. Rejection rates gradually declined over time, from 4.15% in 2017 to 3.42% by 2023. The most frequent reasons for denial involved uncovered services and insufficient clinical justification. Discussion: These findings underscore the critical role of clear coverage definitions, consistent coding, and effective administrative oversight in minimizing denials. Younger retirees, female beneficiaries, and certain service types (dental, laboratory) emerged as particularly vulnerable to rejections, indicating the need for targeted policy refinements. Notably, the downward trend in rejections suggests that AFYA has capacity for adaptive improvements over time. Conclusion: By revealing pivotal factors that drive or mitigate claim rejections, this analysis offers practical guidance for policymakers and healthcare administrators. Standardized electronic forms, provider feedback loops and tighter coverage definitions could trim residual denials without restricting access. AFYA's experience offers transferable lessons for high-income countries seeking to expand private-sector purchasing while containing cost.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.