A retrospective study of insurance coverage status and economic cost of rare diseases in Hainan Province

Rare diseases present a significant economic burden on patients, families, and healthcare systems worldwide. As the prevalence of these diseases rises in China, data regarding their impact, specifically in Hainan Province, is scarce. Thus, this study aims to evaluate insurance coverage, economic costs, and the factors contributing to the burden of rare diseases in Hainan. We employed a bottom-up approach to analyse the prevalence and economic burden from 2019 to 2023, utilising data from the Hainan Provincial Health Commission Databases. We assessed insurance coverage as well as expenditures related to hospitalisation, diagnostics, medications, surgery, and out-of-pocket costs. Of 4,975 patients diagnosed with 99 distinct rare diseases, 83.01% were insured. From 2019 to 2023, the number of patients increased from 760 to 1,328, while economic costs surged from 34.26 million CNY (US$ 4.89 million) to 64.74 million CNY (US$ 8.86 million). Thalassemia major, one of the most prevalent conditions, generated the highest costs. Hospitalisation expenses accounted for 49.16% of the total costs, with out-of-pocket expenses averaging 17.52%. The findings reveal a significant economic burden associated with rare diseases in Hainan, highlighting the necessity for targeted policy interventions. Furthermore, additional research is needed to refine estimates of this economic burden.

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Publication Details

Journal
Scientific Reports
Published
2025-04-17
DOI
https://doi.org/10.1038/s41598-025-97836-0
Citations
4
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
12.52

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article

A retrospective study of insurance coverage status and economic cost of rare diseases in Hainan Province

Bashir Ahmad, John Sieh Dumbuya, Linhong Deng, Jun Lü et al.
4 citations
Scientific Reports
Health Systems, Economic Evaluations, Quality of Life
12.52
article

A retrospective study of insurance coverage status and economic cost of rare diseases in Hainan Province

Bashir Ahmad, John Sieh Dumbuya, Linhong Deng, Jun Lü, Xiuling Chen
article en
4 citations

Abstract

Rare diseases present a significant economic burden on patients, families, and healthcare systems worldwide. As the prevalence of these diseases rises in China, data regarding their impact, specifically in Hainan Province, is scarce. Thus, this study aims to evaluate insurance coverage, economic costs, and the factors contributing to the burden of rare diseases in Hainan. We employed a bottom-up approach to analyse the prevalence and economic burden from 2019 to 2023, utilising data from the Hainan Provincial Health Commission Databases. We assessed insurance coverage as well as expenditures related to hospitalisation, diagnostics, medications, surgery, and out-of-pocket costs. Of 4,975 patients diagnosed with 99 distinct rare diseases, 83.01% were insured. From 2019 to 2023, the number of patients increased from 760 to 1,328, while economic costs surged from 34.26 million CNY (US$ 4.89 million) to 64.74 million CNY (US$ 8.86 million). Thalassemia major, one of the most prevalent conditions, generated the highest costs. Hospitalisation expenses accounted for 49.16% of the total costs, with out-of-pocket expenses averaging 17.52%. The findings reveal a significant economic burden associated with rare diseases in Hainan, highlighting the necessity for targeted policy interventions. Furthermore, additional research is needed to refine estimates of this economic burden.

Scientific ReportsVol. 15(1)
Guangdong Medical College (CN), Affiliated Hospital of Guangdong Medical College Hospital (CN)
National Natural Science Foundation of China
Decent work and economic growth
Openalex Percentile: Top 2%
Health Systems, Economic Evaluations, Quality of Life
12.52
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A retrospective study of insurance coverage status and economic cost of rare diseases in Hainan Province — Bashir Ahmad, John Sieh Dumbuya, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS