Khaled Shaeel Althabaiti, Monica Hunsberger, Sayem Ahmed, Jahangir Khan
Outpatient utilization in KSA showed significant pro-rich income-related inequality. This inequality was more pronounced within PHI than within GHC, particularly among non-Saudis and those with primary and intermediate education. Saudi nationality was the largest positive contributor, while PHI made a small negative contribution to overall inequality. These findings highlight the importance of evaluating Vision 2030 health coverage reforms not only by coverage expansion, but also by whether they reduce inequalities in outpatient healthcare utilization across income groups, supporting progress toward UHC.
BACKGROUND: The Kingdom of Saudi Arabia (KSA) has a dual health coverage system comprising government health coverage (GHC) and private health insurance (PHI). Evidence remains limited on how coverage type and socioeconomic status are associated with outpatient utilization, how utilization is distributed across income groups, and the extent to which income-related inequality is associated with need and non-need factors of healthcare utilization.
OBJECTIVE: To estimate and decompose income-related inequality in outpatient healthcare utilization in KSA by health coverage type and need and non-need factors of healthcare utilization.
METHODS: We analyzed data from the 2018 Saudi Family Health Survey, a nationally representative sample of 8,057 adults aged ≥19 years. Outpatient service utilization in the past 12 months was categorized as a binary variable (0 = no, 1 = yes). Monthly household income was used as the socioeconomic ranking variable in the inequality and decomposition analyses. Income-related inequality was measured using the Erreygers Concentration Index (ECI). A decomposition analysis was then performed to estimate the contributions of need and non-need factors, classified using Andersen's Behavioral Model. These factors included health coverage types categorized as GHC or PHI, demographic, and health-related factors.
RESULTS: Outpatient utilization showed a significant overall pro-rich inequality (ECI = 0.122, p < 0.001). Inequality was greater within the PHI group (ECI = 0.257, p < 0.001) than within the GHC group (ECI = 0.040, p < 0.001). Decomposition analysis showed that Saudi nationality was the largest positive contributor to overall inequality (50.53%), followed by primary education (7.55%), female sex (4.65%), and unmarried status (3.01%). In contrast, residence in the Western region (-7.40%), chronic disease (-4.65%), mediocre self-rated health (-3.86%), and good self-rated health (-2.73%) reduced pro-rich inequality. PHI contributed negatively (-0.92%) to the overall inequality.
CONCLUSION: Outpatient utilization in KSA showed significant pro-rich income-related inequality. This inequality was more pronounced within PHI than within GHC, particularly among non-Saudis and those with primary and intermediate education. Saudi nationality was the largest positive contributor, while PHI made a small negative contribution to overall inequality. These findings highlight the importance of evaluating Vision 2030 health coverage reforms not only by coverage expansion, but also by whether they reduce inequalities in outpatient healthcare utilization across income groups, supporting progress toward UHC.