Catastrophic pharmaceutical expenditure in patients with type 2 diabetes in Iran

Financial Toxicity in Diabetes: The State of What We Know

PURPOSE OF REVIEW

This systematic examination quantifies financial toxicity- the economic burden and related financial distress experienced by patients due to medical costs- in diabetes management globally, analyzing prevalence, mechanisms, and interventions across diverse healthcare systems and geographic contexts.

RECENT FINDINGS

Data indicates 30-60% of diabetes patients experience financial toxicity, with household expenditures ranging from 5 to 40% of income on disease management, and demographic disparities evident. Current intervention strategies demonstrate limited efficacy, particularly in resource-constrained settings, while policy approaches show mixed results across economic contexts. Financial toxicity operates through four identified pathways: direct expenses, indirect costs (productivity/caregiver burden), insurance coverage limitations, and structural access barriers. Research priorities include developing validated measurement instruments for diabetes financial toxicity, implementing contextually appropriate interventions, and establishing causative relationships between financial burden and clinical outcomes through longitudinal studies.

Exploring dental and medicine health expenditures in Iran: financial protection and inequality analysis

BACKGROUND

Healthcare systems must not only improve health outcomes but also protect individuals from financial hardship caused by healthcare costs. This study aimed to investigate financial protection and economic inequality in catastrophic dental healthcare expenditure (CDHE) and catastrophic medicine expenditure (CME) among the insured households through the Social Security Organization (SSO) in Iran.

METHOD

This cross-sectional study gathered data from 1679 insured households across 5 provinces, utilizing a multistage sampling approach. The prevalence of CDHE and CME was assessed by determining the proportion of households spending at least 40% of their capacity to pay on dental care and medications. Logistic regression analysis was used to identify the factors contributing to CDHE and CME. The concentration curve (CC) and concentration index (CI) were employed to visualize and quantify the extent of economic inequality in CDHE and CME. The CI was further decomposed to identify the primary factors driving the observed economic inequality in CDHE and CME.

FINDINGS

The study found that 6.2% (95% confidence interval CI 5.1 to 7.4%) of households experienced CDHE and 4.9% (95% CI 4.0 to 6.0%) experienced CME. The CI for dental costs and medication costs were 0.248 (95% CI 0.115 to 0.381) and was 0.149 (95%CI 0.087 to 0.211), respectively, indicating that these costs were more concentrated among socioeconomically advantaged households. Conversely, the CI for CDHE and CME were -0.185 (95% CI -0.297 to -0.073) and -0.570 (95% CI -0.692 to -0.448), respectively, suggesting that these outcomes were more prevalent among poorer households. The decomposition analysis highlighted that the household wealth index explained 45.4% and 22.5% of the concentration of CDHE and CME among the poor, respectively.

CONCLUSION

The financial burden imposed by out-of-pocket (OOP) payments for dental care and medication was substantial among households insured by the SSO. Expanding insurance coverage for these services could significantly reduce OOP spending and the likelihood of health expenditures leading to poverty, particularly among lower-income households.

Overview of the main methods used for estimating catastrophic health expenditure

Out-of-pocket payments are expenditures borne directly by an individual/household for health services that are not reimbursed by any third-party. Households can experience financial hardship when the burden of such out-of-pocket payments is significant. This financial hardship is commonly measured using the "catastrophic health expenditure" (CHE) metric. CHE has been applied as an indicator in several health sectors and health policies. However, despite its importance, the methods used to measure the incidence of CHE vary across different studies and the terminology used can be inconsistent. In this paper, we introduce and raise awareness of the main approaches used to calculate CHE and discuss critical areas of methodological variation in a global health context. We outline the key features, foundation and differences between the two main methods used for estimating CHE: the budget share and the capacity-to-pay approach. We discuss key sources of variation within CHE calculation and using data from Ethiopia as a case study, illustrate how different approaches can lead to notably different CHE estimates. This variation could lead to challenges when decisionmakers and policymakers need to compare different studies' CHE estimates. This overview is intended to better understand how to interpret and compare CHE estimates and the potential variation across different studies.