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Background: Utilization of maternal healthcare services has a direct bearing on maternal mortality but is contingent on a wide range of socioeconomic factors, including the sex of the household head. This paper studies the role of the sex of the household head in the utilization of maternal healthcare services in India using data from the National Family Health Survey-V (2019–2021). Methods: The outcome variable of this study is maternal healthcare service utilization. To that end, we consider three types of maternal healthcare services: antenatal care, skilled birth assistance, and postnatal care to measure the utilization of maternal healthcare service utilization. The explanatory variable is the sex of the household head and we control for specific characteristics at the individual level, household-head level, household level and spouse level. We then incorporate a bivariate logistic regression on the variables of interest. Results: 24.25% of women from male-headed households have complete utilization of maternal healthcare services while this proportion for women from female-headed households stands at 22.39%. The results from the bivariate logistic regression confirm the significant impact that the sex of the household head has on the utilization of maternal healthcare services in India. It is observed that women from female-headed households in India are 19% (AOR, 0.81; 95% CI: 0.63,1.03) less likely to utilize these services than those from male-headed households. Moreover with higher levels of education, there is a 25% (AOR, 1.25; 95% CI: 1.08,1.44) greater likelihood of utilizing maternal healthcare services. Residence in urban areas, improved wealth quintiles and access to healthcare facilities significantly increases the chances of maternal healthcare utilization. The interaction term between the sex of the household head and the wealth quintile the household belongs to, (AOR, 1.39; 95% CI: 1.02, 1.89) shows that the utilization of maternal healthcare services improves when the wealth quintile of the household improves. Conclusion: The results throw light on the fact that the added expenditure on maternal healthcare services exacerbates the existing financial burden for the economically vulnerable female-headed households. This necessitates the concentration of research and policy attention to alleviate these households from the sexual and reproductive health distresses. Trial Registration: Not Applicable. JEL Classification: D10, I12, J16. [ABSTRACT FROM AUTHOR]

Introduction: Outpatient services are crucial for strengthening primary healthcare and reducing out-of-pocket spending, which has been one of the major causes of impoverishment. So it is also critical to comprehend the people's preferences in accessing primary healthcare facilities, as government primary healthcare facilities in India are underutilized. The current paper explores the factors that construct the individual's decision to seek outpatient care in primary healthcare facilities in India's largest state Rajasthan. Methods: It was a cross-sectional survey conducted in 72 primary sample units of 24 primary health centers in 11 districts of Rajasthan, India, from November 2019 to January 2020. The study selected 368 households through purposive sampling. Out of 368 households, 460 people reported any illness and 326 reported outpatient visit to any health facility in the last 30 days from the date of the survey. Analysis: The focus was on analyzing the data in the context of public and private health facilities to understand the factors influencing people's choice to access outpatient services. The principal component analysis is used to understand the relationship between facility preparedness and OPD uptake. Also, multivariate logistic regression is applied to assess the significant predictors in using primary health facility services. Result: Except for the 29% of patients who received no care, the proportion of patients attended public health facilities was 35%, and the rest were utilizing private health facilities. Those who sought care at PHCs were mostly over 45 years age, non-literate, and from the lowest wealth quintile. Logistic regression suggests that people belong to upper wealth quintile (OR = 0.298; 95% 0.118–0.753) are less likely to visit PHCs for treatment. Also, increase in distance of PHC (OR = 0.203; 95% CI 0.076–0.539) reduces the likelihood of their visit outpatient care. People are 9.7 times (OR = 9.740; 95% CI 2.856–33.217) more likely to visit a PHCs that are better equipped in terms of human resources, equipment, and medicine. Conclusion: The uptake of PHCs depends on several factors, which should be considered to ensure that all segments of society have equitable access to them. Through improved accessibility and quality of service, PHCs can be made more appealing to the larger population. [ABSTRACT FROM AUTHOR]

The 'Cost of Health Services in India (CHSI)' is the first large scale multi-site facility costing study to incorporate evidence from a national sample of both private and public sectors at different levels of the health system in India. This paper provides an overview of the extent of heterogeneity in costs caused by various supply-side factors.A total of 38 public (11 tertiary care and 27 secondary care) and 16 private hospitals were sampled from 11 states of India. From the sampled facilities, a total of 327 specialties were included, with 48, 79 and 200 specialties covered in tertiary, private and district hospitals respectively. A mixed methodology consisting of both bottom-up and top-down costing was used for data collection. Unit costs per service output were calculated at the cost centre level (outpatient, inpatient, operating theatre, and ICU) and compared across provider type and geographical location.The unadjusted cost per admission was highest for tertiary facilities (₹ 5690, 75 USD) followed by private facilities (₹ 4839, 64 USD) and district hospitals (₹ 3447, 45 USD). Differences in unit costs were found across types of providers, resulting from both variations in capacity utilisation, length of stay and the scale of activity. In addition, significant differences in costs were found associated with geographical location (city classification).The reliance on cost information from single sites or small samples ignores the issue of heterogeneity driven by both demand and supply-side factors. The CHSI cost data set provides a unique insight into cost variability across different types of providers in India. The present analysis shows that both geographical location and the scale of activity are important determinants for deriving the cost of a health service and should be accounted for in healthcare decision making from budgeting to economic evaluation and price-setting. [ABSTRACT FROM AUTHOR]

Background: The National Health Mission (NHM), the largest ever publicly funded health programme worldwide, used over half of the national health budget in India and primarily aimed to improve maternal and child health in the country. Though large scale public health investment has improved the health care utilization and health outcomes across states and socio-economic groups in India, little is known on the equity concern of NHM. In this context, this paper examines the utilization pattern and net benefit of public subsidy for institutional delivery by the level of care in India. Methods: Data from the most recent round of the National Family Health Survey (NFHS 4), conducted during 2015–16, was used in the study. A total of 148,645 last birth delivered in a health centre during the 5 years preceding the survey were used for the analyses. Out-of-pocket (OOP) payment on delivery care was taken as the dependent variable and was analysed by primary care and secondary level of care. Benefits Incidence Analysis (BIA), descriptive statistics, concentration index (CI), and concentration curve (CC) were used to do the analysis. Results: Institutional delivery from the public health centres in India is pro-poor and has a strong economic gradient. However, about 28% mothers from richest wealth quintile did not pay for delivery in public health centres compared to 16% among the poorest wealth quintile. Benefit incidence analyses suggests a pro-poor distribution of institutional delivery both at primary and secondary level of care. In 2015–16, at the primary level, about 32.29% of subsidies were used by the poorest, 27.22% by poorer, 20.39% by middle, 13.36% by richer and 6.73% by the richest wealth quintile. The pattern at the secondary level was similar, though the magnitude was lower. The concentration index of institutional delivery in public health centres was − 0.161 [95% CI, − 0.158, − 0.165] compared to 0.296 [95% CI, 0.289, 0.303] from private health centres. Conclusion: Provision and use of public subsidy for institutional delivery in public health centres is pro-poor in India. Improving the quality of service in primary health centres is recommended to increase utilisation and reduce OOP payment for health care in India. [ABSTRACT FROM AUTHOR]

Background: Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data and methods: Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results: Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is not significant. Conclusion: The multidimensionally poor in the poorer regions are more likely to face health shocks and are less likely to afford professional health services. Increasing government spending on health and increasing households' access to health insurance can reduce catastrophic health spending and multidimensional poverty. [ABSTRACT FROM AUTHOR]

Background: Equity and justice in healthcare payment form an integral part of health policy and planning. In the majority of low and middle-income countries (LMICs), healthcare inequalities are further aggravated by Out of Pocket Expenditure (OOPE). This paper examines the pattern of health equity and regional disparities in healthcare spending among Indian states by applying Andersen's behavioural model of healthcare utilization. Methods: The present study uses data from the 66th quinquennial round of Consumer Expenditure Survey, of the National Sample Survey Organization (NSSO), conducted in 2009-10 by Ministry of Statistics and Programme Implementation (MoSPI), Government of India (GoI). To measure equity and regional disparities in healthcare expenditure, states have been categorized under three heads on the basis of monthly OOPE i.e., Category A (OOPE > =INR 100); Category B (OOPE between INR 50 to 99) and Category C (OOPE < INR 50). Multiple Generalised Linear Regression Model (GLRM) has been employed to explore the effect of various socio-economic covariates on the level of OOPE. Results: The gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states Category B (richest/poorest = 14.60), followed by (richest/poorest 11.70) and Category C (richest/poorest 11.40). Results also indicate geographical concentration of lower level healthcare spending among Indian states (e.g., Odisha, Chhattisgarh and all the north-eastern states). Results from the multivariate analysis suggest that people residing in urban areas, having higher economic status, belonging to non-Muslim communities, non-Scheduled Tribes (STs), and non-poor households spend more on healthcare than their counterparts. Conclusions: In spite of various efforts by the government to reduce the burden of healthcare spending, widespread inequalities in healthcare expenditure are prevalent. Households with high healthcare needs (SCs/STs, and the poor) are in a more disadvantaged position in terms of spending on health care. It has also been observed that spending on healthcare was comparatively lower among backward or isolated states. No doubt, the overall social security measures should be enhanced, but at the same time, looking at the regional differences, more priority should be assigned to the disadvantaged states to reduce the burden of OOPE. It is proposed that there is need to increase government spending, especially for the disadvantaged states and population, to minimise the burden of OOPE. [ABSTRACT FROM AUTHOR]

Background: Though Janani Suraksha Yojana (JSY) under National Rural Health Mission (NRHM) is successful in increasing antenatal and natal care services, little is known on the cost coverage of out-of-pocket expenditure (OOPE) on maternal care services post-NRHM period.Methods: Using data from a community-based study of 424 recently delivered women in Rajasthan, this paper examined the variation in OOPE in accessing maternal health services and the extent to which JSY incentives covered the burden of cost incurred. Descriptive statistics and logistic regression analyses are used to understand the differential and determinants of OOPE.Results: The mean OOPE for antenatal care was US$26 at public health centres and US$64 at private health centres. The OOPE (antenatal and natal) per delivery was US$32 if delivery was conducted at home, US$78 at public facility and US$154 at private facility. The OOPE varied by the type of delivery, delivery with complications and place of ANC. The OOPE in public health centre was US$44 and US$145 for normal and complicated delivery, respectively. The share of JSY was 44 % of the total cost per delivery, 77 % in case of normal delivery and 23 % for complicated delivery. Results from the log linear model suggest that economic status, educational level and pregnancy complications are significant predictors of OOPE.Conclusions: Our results suggest that JSY has increased the coverage of institutional delivery and reduced financial stress to household and families but not sufficient for complicated delivery. Provisioning of providing sonography/other test and treating complicated cases in public health centres need to be strengthened. [ABSTRACT FROM AUTHOR]

Background: Rates of perinatal depression (antenatal and postnatal depression) in South Asia are among the highest in the world. The delivery of effective psychological treatments for perinatal depression through existing health systems is a challenge due to a lack of human resources. This paper reports on a trial protocol that aims to evaluate the effectiveness and cost-effectiveness of the Thinking Healthy Programme delivered by peers (Thinking Healthy Programme Peer-delivered; THPP), for women with moderate to severe perinatal depression in rural and urban settings in Pakistan and India.Methods/design: THPP is evaluated with two randomised controlled trials: a cluster trial in Rawalpindi, Pakistan, and an individually randomised trial in Goa, India. Trial participants are pregnant women who are registered with the lady health workers in the study area in Pakistan and pregnant women attending outpatient antenatal clinics in India. They will be screened using the patient health questionnaire-9 (PHQ-9) for depression symptoms and will be eligible if their PHQ-9 is equal to or greater than 10 (PHQ-9 ≥ 10). The sample size will be 560 and 280 women in Pakistan and India, respectively. Women in the intervention arm (THPP) will be offered ten individual and four group sessions (Pakistan) or 6-14 individual sessions (India) delivered by a peer (defined as a mother from the same community who is trained and supervised in delivering the intervention). Women in the control arm (enhanced usual care) will receive health care as usual, enhanced by providing the gynaecologist or primary-health facilities with adapted WHO mhGAP guidelines for depression treatment, and providing the woman with her diagnosis and information on how to seek help for herself. The primary outcomes are remission and severity of depression symptoms at the 6-month postnatal follow-up. Secondary outcomes include remission and severity of depression symptoms at the 3-month postnatal follow-up, functional disability, perceived social support, breastfeeding rates, infant height and weight, and costs of health care at the 3- and 6-month postnatal follow-ups. The primary analysis will be intention-to-treat.Discussion: The trials have the potential to strengthen the evidence on the effectiveness and cost-effectiveness of an evidence-based psychological treatment recommended by the World Health Organisation and delivered by peers for perinatal depression. The trials have the unique opportunity to overcome the shortage of human resources in global mental health and may advance our understanding about the use of peers who work in partnership with the existing health systems in low-resource settings.Trial Registration: Pakistan Trial: ClinicalTrials.gov Identifier: NCT02111915 (9 April 2014) India Trial: ClinicalTrials.gov Identifier: NCT02104232 (1 April 2014). [ABSTRACT FROM AUTHOR]

Background: A peculiar phenomenon of engaging insurance intermediaries for government funded health insurance schemes for the poor, not usually found globally, is gaining ground in India. Rajiv Aarogyasri Scheme launched in the Indian state of Andhra Pradesh, is first largest tax funded community health insurance scheme in the country covering more than 20 million poor families. Aarogyasri Health Care Trust (trust), the scheme administrator, transfers funds to hospitals through two routes one, directly and the other through an insurance intermediary. The objective of this paper is to find out if engaging an insurance intermediary has any effect on cost efficiency of the insurance scheme.Methods: We used payment data of RAS for the period 2007-12, to find out the influence of insurance intermediary on the two variables, benefit cost ratio defined as benefit payment divided by premium payment, and claim denial ratio defined as benefit payment divided by treatment cost. Relationship between scheme expenditure and number of beds empanelled under the scheme is examined. OLS regression is used to perform all analyses.Results: We found that adding an additional layer of insurance intermediary between the trust and hospitals reduced the benefit cost ratio under the scheme by 12.2% (p-value = 0.06). Every addition of 100 beds under the scheme increases the scheme payments by US$ 0.75 million (p-value < 0.001). The gap in claim denial ratio between insurance and trust modes narrowed down from 2.84% in government hospitals to 0.41% in private hospitals (p-value < 0.001).Conclusions: The scheme is a classic case of Roemer's principle in operation. Introduction of insurance intermediary has the twin effects of reduction in benefit payments to beneficiaries, and chocking fund flow to government hospitals. The idea of engaging insurance intermediary should be abandoned. [ABSTRACT FROM AUTHOR]

Background: Universal health coverage through the removal of financial and other barriers to access, particularly for people who are poor, is a global priority. This viewpoint describes the many pathways to catastrophic health expenditure (CHE) for patients with Acute Coronary Syndrome (ACS) based on two case studies and the thematic analysis of field notes regarding 210 patients and their households from a study based in Kerala, India. Discussion: There is evidence of the severe financial impact of non-communicable diseases (NCDs), which is in contradiction to the widely acclaimed Kerala model: Good health at low cost. However, it is important to look beyond the out-of-pocket expenditure (OOPE) and CHE to the possible pathways and identify the triggers that make families vulnerable to CHE. The identified pathways include a primary and secondary loop. The primary pathway describes the direct path by which families experience CHE. These include: 1) factors related to the prevent period that increase the likelihood of experiencing CHE, such as being from the lower socio-economic strata (SES), past financial losses or loans that leave families with no financial shock absorber at the time of illness; 2) factors related to the acute event, diagnosis, treatment and hospitalization and expenditures incurred for the same and; 3) factors related to the post-event period such as loss of gainful employment and means of financing both the acute period and the long-term management particularly through distress financing. The secondary pathway arises from the primary and includes: 1) the impact of distress financing and; 2) the long- and short- term consequences of CHE. These factors ultimately result in a vicious cycle of debt and poverty through noncompliance and repeat acute events. Summary: This paper outlines the direct and indirect pathways by which patients with ACS and their families are trapped in a vicious cycle of debt and poverty. It also contradicts the prevailing impression that only low-income families are susceptible to CHE, distress financing and their aftermaths and underscores the need for a deeper understanding at the micro-level, if Kerala and India as a whole are to undertake the difficult exercise of achieving universal health coverage to successfully tackle its growing NCD burden. [ABSTRACT FROM AUTHOR]

Background: Benefit Incidence Analysis (BIA) is used to understand the distribution of health care utilization and spending in comparison to income distribution. The results can illustrate how effectively governments allocate limited resources towards meeting the needs of the poor. In analyzing the distribution of public spending on inpatient, outpatient, and deliveries, this paper represents the most recent BIA completed in India. Methods: In order to conduct the BIA statistical analysis for this project, 2014 utilization data from the most recently completed Indian National Sample Survey (NSS) was used. Unit costs were estimated for primary care, hospital inpatient, hospital outpatient, and deliveries. Concentration curves and concentration indices were estimated both at the national and state levels. Analyses were reported for overall utilization, as well as for the gross and net benefits for inpatient, outpatient, and deliveries. Results: According to the results, utilization of government inpatient and delivery services is pro-poor. When gross and net benefits are included in the analysis, services become more equal and less pro-poor. Gross benefits, which are measured with state-level unit costs, are virtually equal for all services. Although there are some pro-poor gross benefits trends for national outpatient services, the results also show that the equality of national gross benefits trends hides a significant disparity across Indian States. While a number of Indian States have outpatient gross benefits that are pro-poor, few show pro-poor benefits for inpatient and delivery services. Net benefits, which considers both unit costs for each respective service, and out-of-pocket (OOP) expenditures, trend similarly to gross benefits. In addition, those who use public facilities spend considerable OOP to supplement government services. Conclusions: This BIA reveals that government spending on public health care has not resulted in significantly pro-poor services. While some progress has been made relative to deliveries and outpatient services, inpatient stays are not pro-poor. In addition, national results mask significant disparities across Indian states. [ABSTRACT FROM AUTHOR]

Background: To achieve the Sustainable Development Goals, Indian States have implemented different strategies to arrest high out-of-pocket expenditure (OOPE) and to increase equity into healthcare system. Tamil Nadu (TN) and Rajasthan have implemented free medicine scheme in all public hospitals and West Bengal (WB) has devised Fair Price Medicine Shop (FPMS) scheme, a public-private-partnership model in the state. In this background, the objectives of the paper are to - 1. Study the utilization pattern of public in-patient care facilities for the states, 2. Examine the effectiveness of the strategies adopted by the states to arrest high OOPE and 3. Analyze the extent of equity in public in-patient care services in the states.Methods: National Sample Survey (71st and 60th round) data, Detailed Demand for Grants of the state governments and the National Rural/Urban Health Mission data have been used for the study. Exploratory data analysis and benefit incidence analysis have been applied to estimate the utilization, OOPE and extend of equity in the states.Results: The results show that overall utilization of public facilities in TN and Rajasthan has increased substantially; whereas, utilization of public facility has decreased in WB even among the poorest. In addition, OOPE for both medical and medicine is the highest in WB among three states for public sector hospitalizations. Surprisingly, OOPE on medicine is the highest for the poorest class of WB. Analysis showed that the mismatch between actual need and FPMS drug-list has led to high OOPE in the state. Overall, benefit incidence of public subsidy is the highest among the poorest class in all the states. However, geographical sector-wise inequity in public subsidy distribution persists in the states. Analysis of cost of inpatient care shows that TN provides the maximum subsidy for hospitalization and WB provides the minimum. An inverse relationship between utilization of inpatient care and public subsidy has been observed from the analysis.Conclusion: In conclusion we could say that TN & Rajasthan have successfully implemented their health financing strategies to reduce the health expenditure burden. However, policy-level changes are required to improve the situation in WB. [ABSTRACT FROM AUTHOR]