IMPORTANCE High out-of-pocket expenditure (OOPE) on health in India may limit achieving universal health coverage. A clear insight on the components of health expenditure may be necessary to make allocative decisions to reduce OOPE, and such details by sociodemographic group and state have not been studied in India.OBJECTIVE To analyze the relative contribution of drugs, diagnostic tests, doctor and surgeon fees, and expenditure on other medical services and nonmedical health-related services, such as transport, lodging, and food, by sociodemographic characteristics of patients, geography, and type of illness. DESIGN, SETTING, AND PARTICIPANTSA population-based cross-sectional health consumption survey conducted by the National Sample Survey Organisation in 2018 was analyzed in this crosssectional study. Respondents who provided complete information on costs of medicine, doctors, diagnostics tests, other medical costs, and nonmedical costs were selected. Data were analyzed from August through September 2021. MAIN OUTCOMES AND MEASURES Mean and median share of components (ie, medicine, diagnostic tests, doctor fees, other medical costs, and nonmedical costs) in total health care expenditure and income were calculated. Bivariate survey-weighted mean (with 95% CI) and median (IQR) expenditures were calculated for each component across sociodemographic characteristics. The proportion of total expenditure and income contributed by each cost was calculated for each individual. Mean and median were then used to summarize such proportions at the population level. The association between state net domestic product per capita and component share of each health care service was graphically explored. RESULTS Health expenditure details were analyzed for 43 781 individuals for inpatient costs (27 272 [64.3%] women; 26 830 individuals aged 25-64 years [59.9%]) and 8914 individuals for outpatient costs (4176 [48.2%] women; 4901 individuals aged 25-64 years [54.2%]); most individuals were rural residents (24 106 inpatients [67.0]; 4591 outpatients [63.9%]). Medicines accounted for a mean of 29.1% (95% CI, 28.9%-29.2%) of OOPE among inpatients and 60.3% (95% CI, 59.7%-60.9%) of OOPE among outpatients. Doctor consultation charges were a mean of 15.3% (95% CI, 15.1%-15.4%) of OOPE among inpatients and 12.4% (95% CI, 12.1%-12.6%) of OOPE among outpatients. Diagnostic tests accounted for a mean of 12.3% (95% CI, 12.2%-12.4%) of OOPE for inpatient and 9.2% (95% CI, 8.9%-9.5%) of OOPE for outpatient services. Nonmedical costs accounted for a mean of 23.6% (95% CI, 23.3%-23.8%) of OOPE among inpatients and 14.6% (95% CI, 14.1%-15.1%) of OOPE among outpatients. Mean share of OOPE from doctor consultations and diagnostic test charges increased with socioeconomic status. For example, for the lowest vs highest monthly per capita income quintile among inpatients, doctor consultations accounted for 11.5% (95% CI, 11.1%-11.8%) vs 21.2% (95% CI, 20.8%-21.6%), and diagnostic test charges accounted for 10.9% (95% CI, 10.6%-11.1%) vs 14.3% (continu...

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Supplemental Digital Content is Available in the Text.More than a third of older people in India are often troubled by pain, and more than a quarter of them receive no treatment.

Background The cost of maternity care is seen as the barrier in utilizing maternity care, resulting in high maternal deaths. This study focuses on the distress financing and its coping mechanisms associated with maternity care expenditure in India so that corrective measures can be taken to reduce the burden of maternity care. Methods This study used the National Sample Survey (NSS) data conducted in 20,014–15 (71st round of NSS) and 2017–18(75th round of NSS). We define distress financing as use of formal borrowing, borrowing from friends or family or sale of asser to finance maternity care. Percentage of pregnant/delivered females using distress financing were calculated.. The present study also used multinomial logistic regression with 95% to understand the impact of socio-economic variables on distress financing and concentration index to measure the inequality in maternity care expenditure. Results This study found that the maternity care expenditure has decreased from the INR. 9379 in 2014–15 to INR. 7835 in 2017–18. The percentage of households using distress financing is higher among the poorest (13.2%). Almost 14% of the SC households experience distress financing. Among EAG + A states, particularly in Madhya Pradesh and Uttarakhand, the percentage of households are which experience a high level of distress financing increased from 8.9 to 18.3 and 0.7 to 8.1 from 2014–15 to 2017–18 respectively. The study finds that more urban households (37%) utilized insurance than rural households (26%). Among EAG + A states, 67.9 percent of households were dependent upon household savings, and it was 63.6 percent in the non-EAG states. The households with a high burden of maternity care expenditure were at higher risk of borrowing money to finance the cost of maternity as compared to use of savings/income for the same (relative risk (RR) (R: 2.59; P < 0.01; 95% CI: 2.15–3.13). Mothers belonging to the SC caste were at significantly higher risk (RR: 1.43; P < 0.1; 95% CI: 1.07–1.91). of using borrowings as compared to the use of income/savings. Mothers with college education were 50% more likely to use health insurance as compared to those with primary education. Conclusions The study found that even though many programs for maternity care services are there, the maternity care expenditure, particularly the delivery care expenses, is very high in many states. The study recommends that India should increase subsidized maternity care facilities to decrease catastrophic maternity expenditure among households.