How Does the Change in Household Age-Sex Composition Affect Out of Pocket Healthcare Expenditure of Older Adults in India?

Medical expenses and its determinants in female patients with urological disorder

BACKGROUND

The rising older adult population has led to an increase in the prevalence of chronic diseases and medical expenses. Women tend to have a longer healthy life expectancy than men and are more likely to be exposed to urological disorders around the age of 50, resulting in substantial healthcare expenses throughout their lifetime. Urological disorders often require continuous treatment owing to their high risk of recurrence, contributing to an increased financial burden from medical costs. This study aimed to identify factors influencing medical expense in female patients with urological disorders and propose strategies to alleviate the associated financial burden.

METHODS

We used data from the Korea Health Panel Survey conducted from 2011 to 2016. The final sample comprised 2,932 patients who visited hospitals for urological disorders. To identify the factors influencing medical expense among female patients with urological disorders, we employed a generalized estimating equation model.

RESULTS

The results indicated that younger people and patients with middle-income levels tended to incur higher medical expenses. Furthermore, patients receiving treatment at tertiary hospitals and those enrolled in National Health Insurance also incurred higher health expenses.

CONCLUSIONS

This study suggests that effective management of medical expenses related to urological disorders in women requires improvements in healthcare accessibility to facilitate early detection and continuous disease management. In addition, the findings highlight the potential benefits of digital health and non-face-to-face treatments in addressing these needs.

Does family medicine reduce household health expenditures: evidence from Türkiye

Türkiye introduced a family medicine-centered primary healthcare model in 2005 as part of the Health Transformation Program, which aimed to reduce household healthcare expenditures, improve access to health services, and reduce the crowding-out effect in first-stage hospital institutions. We investigate the impact of the family medicine program on household healthcare expenditures in Türkiye, focusing on doctor visits, medication prescriptions, and hospitalization expenditures. Using data from a large representative household survey, we employ a difference-in-differences approach combined with the entropy-balancing matching technique. Our robust findings show that living in a province exposed to the family medicine program reduced household doctor visit expenditures by over 40 percent. We also find a significant negative association between the family medicine program and expenditures regarding doctor visits and medication prescriptions in the long run. Greater efforts are now needed to ensure the quality of services offered by family health centers, such as improving the doctor-to-patient ratio.

Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1

Background

Multimorbidity has become a norm in low-and middle-income countries such as India requiring notable health system improvements to combat. Urban population is a heterogeneous group where poor are at a risk of facing inequity in accessing healthcare services which can jeopardize our efforts to attain universal health coverage (UHC). We aimed to estimate the prevalence, assess correlates and patterns of multimorbidity among urban poor. Further, we assessed the outcomes of multimorbidity such as healthcare utilization, expenditure and self-rated health.

Methods

Longitudinal Aging Study in India (LASI), wave-1 is a nationally representative survey conducted amongst participants aged ≥45 years in 2017–18. We included 9,327 participants residing in urban areas, categorized as poor based on monthly per capita expenditure. Descriptive statistics computed prevalence with 95% uncertainty interval. Multivariable logistic regression was executed to assess the association between multimorbidity and various correlates, expressed as adjusted odds ratio. An ordinal regression model was run between self-rated health and number of chronic conditions.

Results

The prevalence of multimorbidity was 45.26% among the urban poor. Hypertension and oral morbidities were the most commonly observed dyad. Respondents who were poorer [AOR: 1.27 (1.06–1.51)] had higher chances of having multimorbidity than the poorest. Respondents with a health insurance [AOR: 1.40 (1.14–1.70)] had a higher risk of having multimorbidity. In-patient admission was significantly higher among participants having multimorbidity. Out of pocket expenditure increased while self-rated health deteriorated with each additional morbid condition.

Conclusion

Multimorbidity is found to be increasingly prevalent among urban poor and individuals having health insurance which demonstrates the need to expand healthcare insurance schemes such as Ayushman Bharat for urban poor to achieve UHC.

The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure

Whether families using big data-based digital payments will increase household healthcare expenditure is a subject that needs to be investigated in the era of big data. Based on the data from China Family Panel Studies (CFPS), 24,126 samples from 2014 to 2018 are used to examine the impact and mechanism of big data-based digital payments on household healthcare expenditure. The empirical results of this paper show that the use of digital payments by households can significantly increase household healthcare expenditure with the empowerment of big data. This research employs the instrumental variable method to verify and produce consistent estimation results in order to address potential endogeneity issues such as measurement error and missing variables. We learn via mechanism analysis that household adoption of big data-driven digital payments can remove credit limitations and build social capital, resulting in higher household health-care spending. We also perform a heterogeneity analysis. The findings reveal that when a family's traditional financial accessibility is high, the head of the household is young or middle-aged, and the head of the household has a higher level of education, digital payment will play a larger role in encouraging household healthcare expenditure. The conclusions of this paper are still solid after changing the indicators of household healthcare expenditure substituting the indicators of digital payment, and adjusting the variables. As a result, this article provides micro-evidence for the usage of digital payments by households to enhance healthcare spending.