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Aam Admi Mohalla Clinics (AAMCs) were introduced in Delhi in 2015 as neighbourhood clinics to strengthen the delivery of primary care. To inform the policies on government investments for outpatient care, this study estimated the cost of outpatient care per visit in Delhi for 2019–20 for AAMCs and compared it with urban primary health centres (UPHCs), public hospitals, private clinics and private hospitals. Facility costs for AAMCs and UPHCs were also estimated. Using the data from a national health survey, government annual budgets and reports, a modified top-down methodology was adopted to measure the true cost of public facilities, taking into account both government expenditure and out-of-pocket expenditure (OOPE). Inflation-adjusted OOPE was used to measure the cost of private facilities. The cost per visit at a private clinic at ₹1146 (US$16) was more than 3-times higher than that at a UPHC (₹325/US$5) and 8-times higher than that at AAMCs (₹143/US$2.0). These costs were ₹1099 (US$15) and ₹1818 (US$25) at public and private hospitals respectively. The annual economic cost per facility of a UPHC at ₹ 9 280 000/$130 000 is ∼4-times that at AAMC (₹2 474 000/$35 000). Unit costs are found to be lower at AAMCs. Utilization for outpatient care has shifted in favour of public primary care facilities. Higher investment in public primary care facilities with expanded services for prevention and promotion, upscaled infrastructure and a gate-keeping mechanism can strengthen the delivery of primary care and promote universal health care at a lower cost.

Background Aam Aadmi Mohalla Clinics (AAMC) are the community level public primary care facilities recently introduced to strengthen primary care in Delhi, India by bringing affordable healthcare close to home. Objectives This study looks at the primary care attributes of AAMC from a patient perspective, to assess their features, strengths and weaknesses. Methods Using a primary care survey tool, a cross-sectional survey of 360 users was conducted at 18 facilities across 9 districts of Delhi to gather information on six dimensions of primary care delivery. Thematic analysis of responses to quantitative, multiple-choice and Likert scale questions using percentage of respondents in each category; and a strengths, weaknesses, opportunities and suggestions (SWOS) framework, was used to examine the primary care attributes. Results AAMCs have done well in improving proximity, availability, physical and financial access to primary care with respondents reporting their residence within 1 kilometre of AAMCs (95%), physician being available (100%), free drugs in stock (99%). Service delivery is however not comprehensive with missing preventive care. Respondents reported missing gatekeeping, weak referral mechanism (6–19%), and low physician’s familiarity with their overall health (2%). Conclusion AAMCs have brought affordable healthcare with free medicines and diagnostics to neighbourhood. There is an opportunity for attaining universal healthcare that is responsive to user needs through provision of comprehensive care. Compulsory enrolment of neighbourhood population with an electronic database of patients has an immense potential to improve longitudinality and coordination of care.

Improving investments in primary health care has become a mounting priority in the context of Universal Health Coverage and India’s National Health Policy 2017 goal to provide cost-effective care. The paper uses the India National Health Accounts, health care providers and health care functions classifications, to allocate current health expenditures (CHE) to primary, secondary and tertiary (PST) care and analyse the trends and composition of PST expenditures between 2013–2014 and 2016–2017. Findings reveal that 45.2% of CHE was spent on primary care in 2016–2017. The government spends 52% of its CHE for primary care. Private spending on primary care has declined from 44% to 41% during the study period. Disaggregate analysis shows that 41% of primary care expenditures were on medicines, 29% on curative care and 15% on preventive care services. About 32% of primary care expenditures were spent at government facilities/providers as compared to 10% at private facilities/doctors. Private sector share of secondary care (38%) and tertiary care (75%) reinforces the role of private sector in providing secondary and tertiary care services. In cognisance of national and international goals, an additional investment of 0.7% of gross domestic product or additional US$11 (₹754) per capita would be required in primary care.

Out-of-pocket expenditures on medicines (ME) form a large share of the total out-of-pocket expenditure (OOPE) and pose financial risks for Indian households. Using repeated cross-section analysis of national health surveys for 2014 and 2017–2018, change in financial risk due to ME is examined. Logit regression is used to look at the factors associated with financial risk due to medicine expenditure. Households incurring ME declined by 7%. Per capita monthly ME declined to ₹80 (US$1.25, 95% CI: 78–82) from ₹111 (US$1.74, 95% CI: 108–114). Catastrophic headcount declined to 8.6% from 13.5%, but the mean positive overshoot remained constant at ₹9.5 at the 10% threshold. Impoverishment headcount also declined to 1.4% from 2.2%, and 6.1% persons were immiserated in 2017–2018. Distribution of ME and catastrophe continued to be pro-rich, but impoverishment was greater in poorer households. Among states, the headcount of catastrophe was highest in Kerala, and Odisha had the greatest impoverishment in 2017–2018. Cancer patients faced the largest catastrophe, and tuberculosis patients faced the largest impoverishment due to ME. The odds ratio of financial vulnerability was 2.91 (95% CI: 2.5–3.3) for households with more than one member incurring ME, 1.82 (95% CI: 1.6–2.1) for households with chronic disease patients, and 1.6 (95% CI: 1.4–1.8) for private care utilisation. We conclude that declining OOPE led to a decline in financial risk due to ME.

Various estimates of impoverishment on account of out-of-pocket expenditure (OOPE) on health are available for India, covering different time periods, but there is a void in terms of comparable estimates. This article uses national level surveys conducted by National Sample Survey Organization for measurement of living standards (Consumption Expenditure Survey [CES]) for 2004–2005 and 2011–2012 and Health and Morbidity Survey (HMS) for 2004 and 2014 to quantify the trends in impoverishment estimates over time and identify the factors explaining these trends. Using consistent methodology, it is estimated that the increase in the number of persons impoverished due to OOPE using HMS is 19.78 million (from 77.9 million to 97.78 million) between 2004 and 2014, while using CES, the increase is 2.90 million (from 51.48 to 54.38 million) between 2004–2005 and 2011–2012. Expenditure on outpatient care including drugs led to 72 million people being pushed below poverty line in 2014. Most of the increase in impoverishment has come in lower income quintiles both in rural and urban areas. Government needs to focus on reducing OOPE for bottom three income quintiles and more specifically the household expenditure on medicines.

Site-specific delivery of therapeutics promises better outcomes in the treatment of diseases. A small ligand, anisamide, has been shown to specifically bind sigma receptors highly overexpressed on prostate cancer cells, one of the leading cancers causing deaths worldwide. Here, anisamide-tethered polyethylenimine polymers (AP) have been synthesized and evaluated for their capability to transport nucleic acid across the cell membrane. A series of modified polymers (AP-1 to AP-4) was synthesized, physicochemically characterized, and evaluated for their transfection efficiency and cytotoxicity. Postconjugation, there was a marginal decrease in the buffering capacity; however, it did not diminish the ultimate objective of the study rather improved the transfection efficiency and decreased the cytotoxicity making these polymers as efficient and safe vectors for nucleic acid delivery. All the modified polymers displayed enhanced capability to deliver DNA inside the cells. Among the series, the modified polymer, AP-4 (10% attempted substitution), exhibited the highest transfection in HEK293 cells having abundant sigma receptors with minimal cytotoxicity. The projected polymer also showed complete protection of bound DNA against enzymatic degradation. Altogether, the results demonstrated targeting ability of the proposed polymers to deliver nucleic acid to sigma receptor–bearing cells in vitro.

Introduction Serious bacterial neonatal infections are a major cause of global neonatal mortality. While hospitalized treatment is recommended, families cannot access inpatient treatment in low resource settings. Two parallel randomized control trials were conducted at five sites in three countries (Democratic Republic of Congo, Kenya, and Nigeria) to compare the effectiveness of treatment with experimental regimens requiring fewer injections with a reference regimen A (injection gentamicin plus injection procaine penicillin both once daily for 7 days) on the outpatient basis provided to young infants (0–59 days) with signs of possible serious bacterial infection (PSBI) when the referral was not feasible. Costs were estimated to quantify the financial implications of scaleup, and cost-effectiveness of these regimens. Methods Direct economic costs (including personnel, drugs and consumable costs) were estimated for identification, prenatal and postnatal visits, assessment, classification, treatment and follow-up. Data on time spent by providers on each activity was collected from 83% of providers. Indirect marginal financial costs were estimated for non-consumables/capital, training, transport, communication, administration and supervision by considering only a share of the total research and health system costs considered important for the program. Total economic costs (direct plus indirect) per young infant treated were estimated based on 39% of young infants enrolled in the trial during 2012 and the number of days each treated during one year. The incremental cost-effectiveness ratio was calculated using treatment failure after one week as the outcome indicator. Experimental regimens were compared to the reference regimen and pairwise comparisons were also made. Results The average costs of treating a young infant with clinical severe infection (a sub-category of PSBI) in 2012 was lowest with regimen D (injection gentamicin once daily for 2 days plus oral amoxicillin twice daily for 7 days) at US$ 20.9 (95% CI US$ 16.4–25.3) or US$ 32.5 (2018 prices). While all experimental regimens B (injection gentamicin once daily plus oral amoxicillin twice daily, both for 7 days), regimen C (once daily of injection gentamicin injection plus injection procaine penicillin for 2 days, thereafter oral amoxicillin twice daily for 5 days) and regimen D were found to be more cost-effective as compared with the reference regimen A; pairwise comparison showed regimen D was more cost-effective than B or C. For fast breathing, the average cost of treatment with regimen E (oral amoxicillin twice daily for 7 days) at US$ 18.3 (95% CI US$ 13.4–23.3) or US$ 29.0 (2018 prices) was more cost-effective than regimen A. Indirect costs were 32% of the total treatment costs. Conclusion Scaling up of outpatient treatment for PSBI when the referral is not feasible with fewer injections and oral antibiotics is cost-effective for young infants and can lead to increased access to treatment resulting in potential reductions in neonatal mortality. Clinical trial registration The trial was registered with Australian New Zealand Clinical Trials Registry under ID ACTRN 12610000286044.

Noncommunicable diseases (NCDs) have become a major public health problem in India accounting for 62% of the total burden of foregone DALYs and 53% of total deaths. In this paper, we review the social and economic impact of NCDs in India. We outline this impact at household, health system and the macroeconomic level. Cardiovascular diseases (CVDs) figure at the top among the leading ten causes of adult (25-69 years) deaths in India. The effects of NCDs are inequitable with evidence of reversal in social gradient of risk factors and greater financial implications for the poorer households in India. Out-of-pocket expenditure associated with the acute and long-term effects of NCDs is high resulting in catastrophic health expenditure for the households. Study in India showed that about 25% of families with a member with CVD and 50% with cancer experience catastrophic expenditure and 10% and 25%, respectively, are driven to poverty. The odds of incurring catastrophic hospitalization expenditure were nearly 160% higher with cancer than the odds of incurring catastrophic spending when hospitalization was due to a communicable disease. These high numbers also pose significant challenge for the health system for providing treatment, care and support. The proportion of hospitalizations and outpatient consultations as a result of NCDs rose from 32% to 40% and 22% to 35%, respectively, within a decade from 1995 to 2004. In macroeconomic term, most of the estimates suggest that the NCDs in India account for an economic burden in the range of 5-10% of GDP, which is significant and slowing down GDP thus hampering development. While India is simultaneously experiencing several disease burdens due to old and new infections, nutritional deficiencies, chronic diseases, and injuries, individual interventions for clinical care are unlikely to be affordable on a large scale. While it is clear that "treating our way out" of the NCDs may not be the efficient way, it has to be strongly supplemented with population-based services aimed at health promotion and action on social determinants of health along with individual services. Since health sector alone cannot deal with the "chronic emergency" of NCDs, a multi-sectoral action addressing the social determinants and strengthening of health systems for universal coverage to population and individual services is required.

Trial designThree feeding regimens—centrally produced ready-to-use therapeutic food, locally produced ready-to-use therapeutic food, and augmented, energy-dense, home-prepared food—were provided in a community setting for children with severe acute malnutrition (SAM) in the age group of 6–59 months in an individually randomised multicentre trial that enrolled 906 children. Foods, counselling, feeding support and treatment for mild illnesses were provided until recovery or 16 weeks.MethodsCosts were estimated for 371 children enrolled in Delhi in a semiurban location after active survey and identification, enrolment, diagnosis and treatment for mild illnesses, and finally treatment with one of the three regimens, both under the research and government setting. Direct costs were estimated for human resources using a price times quantity approach, based on their salaries and average time taken for each activity. The cost per week per child for food, medicines and other consumables was estimated based on the total expenditure over the period and children covered. Indirect costs for programme management including training, transport, non-consumables, infrastructure and equipment were estimated per week per child based on total expenditures for research study and making suitable adjustments for estimations under government setting.ResultsNo significant difference in costs was found across the three regimens per covered or per treated child. The average cost per treated child in the government setting was estimated at US$56 (ConclusionHome-based management of SAM with a locally produced ready-to-use therapeutic food is feasible, acceptable, affordable and very cost-effective in terms of the disability-adjusted life years saved and gross national income per capita of the country. The treatment of SAM at home needs serious attention and integration into the existing health system, along with actions to prevent SAM.Trial registration numberNCT01705769; Pre-results.

We estimate the distributional incidence of health care financing in 13 Asian territories that account for 55% of the Asian population. In all territories, higher-income households contribute more to the financing of health care. The better-off contribute more as a proportion of ability to pay in most low- and lower-middle-income territories. Health care financing is slightly regressive in three high-income economies with universal social insurance. Direct taxation is the most progressive source of finance and is most so in poorer economies. In universal systems, social insurance is proportional to regressive. In high-income economies, the out-of-pocket (OOP) payments are proportional or regressive while in low-income economies the better-off spend relatively more OOP. But in most low-/middle-income countries, the better-off not only pay more, they also get more health care.

The article compares the incidence of public healthcare across 11 Asian countries and provinces, testing the dominance of healthcare concentration curves against an equal distribution and Lorenz curves and across countries. The analysis reveals that the distribution of public healthcare is prorich in most developing countries. That distribution is avoidable, but a propoor incidence is easier to realize at higher national incomes. The experiences of Malaysia, Sri Lanka, and Thailand suggest that increasing the incidence of propoor healthcare requires limiting the use of user fees, or protecting the poor effectively from them, and building a wide network of health facilities. Economic growth may not only relax the government budget constraint on propoor policies but also increase propoor incidence indirectly by raising richer individuals' demand for private sector alternatives.

India spends a high proportion of its gross domestic product (GDP) on health care but is still poor in terms of health outcomes as compared to countries at a similar level of development. It is, therefore, extremely important to understand the financial dimensions of the health sector to enable policy makers to take wise decisions in this sector. Taking the case of Karnataka, a state in India, this article seeks to estimate the total health expenditure as a proportion of the state domes tic product (SDP); examine the role of private and public sectors as financiers and providers of health services; and estimate health expenditure by different income classes of beneficiaries, and functions like preventive and curative care. Using National Health Accounts (NHA) as a tool of analysis, this article presents the results for 1993-94. It indicates that 76 per cent of health sector revenues come from private sources, of which almost 50 per cent go to private providers and 21 per cent are spent on drugs. Further, 7 per cent of household out-of-pocket expenditure is used as non-drug expenditure for using government facilities for out-patient and in-patient treatment. This has important policy implications for the government. The role of financial intermediaries, especially the insurance sector, is also highlighted in the analysis. A further analysis by income categories and functional classifications is expected to highlight important results.

Donor nations and philanthropic organizations increasingly require that funds provided for a specific health priority such as HIV should supplement domestic spending on that priority—a concept known as “additionality.” We investigated the “additionality” concept using data from Honduras, Rwanda, and Thailand, and we found that the three countries increased funding for HIV in response to increased donor funding. In contrast, the study revealed that donors, faced with increased Global Fund resources for HIV in certain countries, tended to decrease their funding for HIV or shift funds for use in non-HIV health areas. More broadly, we found many problems in the measurement and interpretation of additionality. These findings suggest that it would be preferable for donors and countries to agree on how best to use available domestic and external funds to improve population health, and to develop better means of tracking outcomes, than to try to develop more sophisticated methods to track additionality.

Out-of-pocket (OOP) expenditure on health care has significant implications for poverty in many developing countries. This paper aims to assess the differential impact of OOP expenditure and its components, such as expenditure on inpatient care, outpatient care and on drugs, across different income quintiles, between developed and less developed regions in India. It also attempts to measure poverty at disaggregated rural-urban and state levels. Based on Consumer Expenditure Survey (CES) data from the National Sample Survey (NSS), conducted in 1999-2000, the share of households' expenditure on health services and drugs was calculated. The number of individuals below the state-specific rural and urban poverty line in 17 major states, with and without netting out OOP expenditure, was determined. This also enabled the calculation of the poverty gap or poverty deepening in each region. Estimates show that OOP expenditure is about 5% of total household expenditure (ranging from about 2% in Assam to almost 7% in Kerala) with a higher proportion being recorded in rural areas and affluent states. Purchase of drugs constitutes 70% of the total OOP expenditure. Approximately 32.5 million persons fell below the poverty line in 1999-2000 through OOP payments, implying that the overall poverty increase after accounting for OOP expenditure is 3.2% (as against a rise of 2.2% shown in earlier literature). Also, the poverty headcount increase and poverty deepening is much higher in poorer states and rural areas compared with affluent states and urban areas, except in the case of Maharashtra. High OOP payment share in total health expenditures did not always imply a high poverty headcount; state-specific economic and social factors played a role. The paper argues for better methods of capturing drugs expenditure in household surveys and recommends that special attention be paid to expenditures on drugs, in particular for the poor. Targeted policies in just five poor states to reduce OOP expenditure could help to prevent almost 60% of the poverty headcount increase through OOP payments.