HEALTH OUTCOMES AND IMPLEMENTATION EFFECTIVENESS OF THE ANKYLOSING SPONDYLITIS RURAL HEALTH PROJECT IN CHINA: A PROSPECTIVE COHORT STUDY FROM HEALTH EQUITY PERSPECTIVE
Author(s)
Jiaqi Shi, Master, Xinyue Yuan, Bachelor, MING HU, PhD;
West China School of Pharmacy, Sichuan University, Chengdu, China
West China School of Pharmacy, Sichuan University, Chengdu, China
Presentation Documents
OBJECTIVES: Ankylosing spondylitis (AS) Rural Health Project, implemented by the National Health Commission of China. It offers subsidies for biologic treatment and deploys medical experts to primary care settings to deliver free clinics, screening, and patient education activities. This study aims to evaluate how health outcomes are distributed and to assess the project’s impact on health equity
METHODS: Data were extracted from the project cohort between January and June 2024. Socioeconomic status (SES) was constructed by combining individual-level economic indicators with regional economic level. Health outcomes were evaluated using incremental net health benefit (INHB) and AS quality-of-life score (AS-QoL). INHB was defined as health gains minus opportunity costs, while AS-QoL was a composite index derived by standardizing four instruments (EQ-5D-5L, SF-36, BASDAI, and BASFI). Concentration curves (CC) and concentration index (CI) were first constructed using the cumulative population proportion ranked by SES and the cumulative AS-QoL. Latent class analysis (LCA) was then applied to identify SES subgroups based on item response probabilities. Finally, aggregate distributional cost-effectiveness analysis (aDCEA) was used to assess the distribution of INHB across SES subgroups.
RESULTS: LCA indicated that a three-class solution provided the best model fit, with the lowest BIC (16666.23). SES was therefore classified into three subgroups (low, medium, and high), with 27.9%, 36.5%, and 35.6% of patients assigned to each class, respectively. Before implementation, the CI slightly but significantly decreased from 0.000459918 to 0.000426257 (p < 0.05), with the CC moving closer to the line of equality. The total INHB of the program was 3.92 QALYs (low-SES group:1.84 QALYs, the medium-SES group:1.46 QALYs, high-SES group:0.62 QALYs).
CONCLUSIONS: These findings suggest that the program primarily benefited patients with lower SES and contributed to reducing pre-existing inequalities in the distribution of health resources.
METHODS: Data were extracted from the project cohort between January and June 2024. Socioeconomic status (SES) was constructed by combining individual-level economic indicators with regional economic level. Health outcomes were evaluated using incremental net health benefit (INHB) and AS quality-of-life score (AS-QoL). INHB was defined as health gains minus opportunity costs, while AS-QoL was a composite index derived by standardizing four instruments (EQ-5D-5L, SF-36, BASDAI, and BASFI). Concentration curves (CC) and concentration index (CI) were first constructed using the cumulative population proportion ranked by SES and the cumulative AS-QoL. Latent class analysis (LCA) was then applied to identify SES subgroups based on item response probabilities. Finally, aggregate distributional cost-effectiveness analysis (aDCEA) was used to assess the distribution of INHB across SES subgroups.
RESULTS: LCA indicated that a three-class solution provided the best model fit, with the lowest BIC (16666.23). SES was therefore classified into three subgroups (low, medium, and high), with 27.9%, 36.5%, and 35.6% of patients assigned to each class, respectively. Before implementation, the CI slightly but significantly decreased from 0.000459918 to 0.000426257 (p < 0.05), with the CC moving closer to the line of equality. The total INHB of the program was 3.92 QALYs (low-SES group:1.84 QALYs, the medium-SES group:1.46 QALYs, high-SES group:0.62 QALYs).
CONCLUSIONS: These findings suggest that the program primarily benefited patients with lower SES and contributed to reducing pre-existing inequalities in the distribution of health resources.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
CO59
Topic
Clinical Outcomes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, SDC: Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal)