Making the health system work for over 25 million births annually: drivers of the notable decline in maternal and newborn mortality in India.

INTRODUCTION: India's progress in reducing maternal and neonatal mortality since the 1990s was faster than the regional average. We systematically analysed how national health policies, services for maternal and newborn health, and socioeconomic contextual changes, drove these mortality reductions. METHODS: The study's mixed-methods design integrated quantitative trend analyses of mortality, intervention coverage and equity since the 1990s, using the sample registration system and national surveys, with interpretive understandings from policy documents and 13 key informant interviews. RESULTS: India's maternal mortality ratio (MMR) declined from 412 to 103 maternal deaths per 100 000 live births between 1997-1998 and 2017-2019. The neonatal mortality rate (NMR) declined from 46 to 22 per 1000 live births between 1997 and 2019. The average annual rate of mortality reduction increased over time. During this period, coverage of any antenatal care (57%-94%), quality antenatal care (37%-85%) and institutional delivery (34%-90%) increased, as did caesarean section rates among the poorest tertile (2%-9%); these coverage gains occurred primarily in the government (public) sector. The fastest rates for increasing coverage occurred during 2005-2012.The 2005-2012 National Rural Health Mission (which became the National Health Mission in 2012) catalysed bureaucratic innovations, additional resources, pro-poor commitments and accountability. These efforts occurred alongside smaller family sizes and improvements in macroeconomic growth, mobile and road networks, women's empowerment, and nutrition. These together reduced high-risk births and improved healthcare access, particularly among the poor. CONCLUSION: Rapid reduction in NMR and MMR in India was accompanied by increased coverage of maternal and newborn health interventions. Government programmes strengthened public sector services, thereby expanding the reach of these interventions. Simultaneously, socioeconomic and demographic shifts led to fewer high-risk births. The study's integrated methodology is relevant for generating comprehensive knowledge to advance universal health coverage.

A tale of two exemplars: the maternal and newborn mortality transitions of two state clusters in India.

BACKGROUND: India's progress in reducing maternal and newborn mortality since the 1990s has been exemplary across diverse contexts. This paper examines progress in two state clusters: higher mortality states (HMS) with lower per capita income and lower mortality states (LMS) with higher per capita income. METHODS: We characterised state clusters' progress in five characteristics of a mortality transition model (mortality levels, causes, health intervention coverage/equity, fertility and socioeconomic development) and examined health policy and systems changes. We conducted quantitative trend analyses, and qualitative document review, interviews and discussions with national and state experts. RESULTS: Both clusters reduced maternal and neonatal mortality by over two-thirds and half respectively during 2000-2018. Neonatal deaths declined in HMS most on days 3-27, and in LMS on days 0-2. From 2005 to 2018, HMS improved coverage of antenatal care with contents (ANCq), institutional delivery and postnatal care (PNC) by over three-fold. In LMS, ANCq, institutional delivery and PNC rose by 1.4-fold. C-sections among the poorest increased from 1.5% to 7.1% in HMS and 5.6% to 19.4% in LMS.Fewer high-risk births (to mothers <18 or 36+ years, birth interval <2 years, birth order 3+) contributed 15% and 6% to neonatal mortality decline in HMS and LMS, respectively. Socioeconomic development improved in both clusters between 2005 and 2021; HMS saw more rapid increases than LMS in women's literacy (1.5-fold), household electricity (by 2-fold), improved sanitation (3.2-fold) and telephone access (6-fold).India's National (Rural) Health Mission's financial and administrative flexibility allowed states to tailor health system reforms. HMS expanded public health resources and financial schemes, while LMS further improved care at hospitals and among the poorest. CONCLUSION: Two state clusters in India progressed in different mortality transitions, with efforts to maximise coverage at increasingly advanced levels of healthcare, alongside socioeconomic improvements. The transition model characterises progress and guides further advances in maternal and newborn survival.

Improving Community Health Worker Compensation: A Case Study From India Using Quantitative Projection Modeling and Incentive Design Principles.

INTRODUCTION: Although community health workers (CHWs) are effective at mobilizing important health behaviors, there is limited evidence on how financial incentive systems can best be designed to drive their effectiveness. This study intends to bridge this evidence gap by analyzing the compensation model of India's accredited social health activist (ASHA) program and identifying areas of improvement in the system's design and implementation. METHODS: We analyze the ASHA program in Uttar Pradesh, India. ASHAs receive compensation through a mix of program-linked, performance-based, and routine activity-based incentive structures. Using multiple data sources, including a novel linked household and ASHA survey, we estimate ASHA performance-linked incentive earnings under different scenarios of ASHA actions and household behaviors. Juxtaposing statistical projection models and actual government payments, we identified which incentives promised the highest payments, which were claimed or not, which could be claimed more by increasing ASHA actions, and which were paid despite not meeting payment criteria. We also report findings on ASHA awareness of and experiences with claiming incentives. RESULTS: We find crucial gaps and implementation challenges in the ASHA incentive structure. ASHAs could double their earnings by completing certain tasks within their control. ASHAs may also be paid for partial completion of activities, as incentives are paid in lump sums for a series of activities rather than for each activity. Family planning incentives have the largest gap between potential and actual earnings. Incentivizing ASHAs for achieving certain health outcomes is inefficient, as no clear linkage was found between the achievability of such health outcomes and the claim amounts. CONCLUSION: There are several opportunities for improving CHW compensation, from improving the incentive claims process to shifting focus to achievable outcomes. Optimizing incentive system designs can further enhance CHW effectiveness globally to affect key health behaviors.

Associations between community health workers' home visits and education-based inequalities in institutional delivery and perinatal mortality in rural Uttar Pradesh, India: a cross-sectional study.

INTRODUCTION: India's National Health Mission has trained community health workers called Accredited Social Health Activists (ASHAs) to visit and counsel women before and after birth. Little is known about the extent to which exposure to ASHAs' home visits has reduced perinatal health inequalities as intended. This study aimed to examine whether ASHAs' third trimester home visits may have contributed to equitable improvements in institutional delivery and reductions in perinatal mortality rates (PMRs) between women with varying education levels in Uttar Pradesh (UP) state, India. METHODS: Cross-sectional survey data were collected from a representative sample of 52 615 women who gave birth in the preceding 2 months in rural areas of 25 districts of UP in 2014-2015. We analysed the data using generalised linear modelling to examine the associations between exposure to home visits and education-based inequalities in institutional delivery and PMRs. RESULTS: Third trimester home visits were associated with higher institutional delivery rates, in particular public facility delivery rates (adjusted risk ratio (aRR) 1.32, 95% CI 1.30 to 1.34), and to a lesser extent private facility delivery rates (aRR 1.09, 95% CI 1.04 to 1.13), after adjusting for confounders. Associations were stronger among women with lower education levels. Having no compared with any third trimester home visits was associated with higher perinatal mortality (aRR 1.18, 95% CI 1.09 to 1.28). Having any versus no visits was more highly associated with lower perinatal mortality among women with lower education levels than those with the most education, and most notably among public facility births. CONCLUSIONS: The results suggest that ASHAs' home visits in the third trimester contributed to equitable improvements in institutional deliveries and lower PMRs, particularly within the public sector. Broader strategies must reinforce the role of ASHAs' home visits in reaching the sustainable development goals of improving maternal and newborn health and leaving no one behind.

Closing the gap on institutional delivery in northern India: a case study of how integrated machine learning approaches can enable precision public health.

INTRODUCTION: Meeting ambitious global health goals with limited resources requires a precision public health (PxPH) approach. Here we describe how integrating data collection optimisation, traditional analytics and causal artificial intelligence/machine learning (ML) can be used in a use case for increasing hospital deliveries of newborns in Uttar Pradesh, India. METHODS: Using a systematic behavioural framework we designed a large-scale survey on perceptual, interpersonal and structural drivers of women's behaviour around childbirth (n=5613). Multivariate logistic regression identified factors associated with institutional delivery (ID). Causal ML determined the cause-and-effect ordering of these factors. Variance decomposition was used to parse sources of variation in delivery location, and a supervised learning algorithm was used to distinguish population subgroups. RESULTS: Among the factors found associated with ID, the causal model showed that having a delivery plan (OR=6.1, 95% CI 6.0 to 6.3), believing the hospital is safer than home (OR=5.4, 95% CI 5.1 to 5.6) and awareness of financial incentives were direct causes of ID (OR=3.4, 95% CI 3.3 to 3.5). Distance to the hospital, borrowing delivery money and the primary decision-maker were not causal. Individual-level factors contributed 69% of variance in delivery location. The segmentation analysis showed four distinct subgroups differentiated by ID risk perception, parity and planning. CONCLUSION: These findings generate a holistic picture of the drivers and barriers to ID in Uttar Pradesh and suggest distinct intervention points for different women. This demonstrates data optimised to identify key behavioural drivers, coupled with traditional and ML analytics, can help design a PxPH approach that maximise the impact of limited resources.

Facilities are substantially more influential than care providers in the quality of delivery care received: a variance decomposition and clustering analysis in Kenya, Malawi and India.

INTRODUCTION: Improving the quality of care during childbirth is essential for reducing neonatal and maternal mortality. One barrier to improving quality of care is understanding the appropriate level to target interventions. We examine quality of care data during labour and delivery from multiple countries to assess whether quality varies primarily from nurse to nurse within the same facility, or primarily between facilities. METHODS: To assess the relative contributions of nurses and facilities to variance in quality of care, we performed a variance decomposition analysis using a linear mixed effect model on two data sources: (1) the number of vital signs assessed for women in labour from a study of nurse practices in Uttar Pradesh, India; 2) broad-scale indices of respectful and competent care generated from Service Provision Assessments in Kenya and Malawi. We used unsupervised clustering, a data mining technique that groups objects together based on similar characteristics, to identify groups of facilities that displayed distinct patterns of vital signs assessment behaviour. RESULTS: We found 3-10 times more variance in quality of care was explained by the facility where a patient received care than by the nurse who provided it. The unsupervised clustering analysis revealed groups of facilities with highly distinct patterns of vital signs assessment, even when overall rates of vital signs assessments were similar (eg, some facilities consistently test fetal heart rate, but not other vitals, others only blood pressure). CONCLUSION: Facilities within a region can vary substantially in the quality of care they provide to women in labour, but within a facility, nurses tend to provide similar care. This holds true both for care that can be influenced by equipment availability and technical training (eg, vital signs assessment), as well as cultural aspects (eg, respectful care).

Community mobilization, empowerment and HIV prevention among female sex workers in south India.

BACKGROUND: While community mobilization has been widely endorsed as an important component of HIV prevention among vulnerable populations such as female sex workers (FSWs), there is uncertainty as to the mechanism through which it impacts upon HIV risk. We explored the hypothesis that individual and collective empowerment of FSW is an outcome of community mobilization, and we examined the means through which HIV risk and vulnerability reduction as well as personal and social transformation are achieved. METHODS: This study was conducted in five districts in south India, where community mobilization programs are implemented as part of the Avahan program (India AIDS Initiative) of the Bill & Melinda Gates Foundation. We used a theoretically derived "integrated empowerment framework" to conduct a secondary analysis of a representative behavioural tracking survey conducted among 1,750 FSWs. We explored the associations between involvement with community mobilization programs, self-reported empowerment (defined as three domains including power within to represent self-esteem and confidence, power with as a measure of collective identity and solidarity, and power over as access to social entitlements, which were created using Principal Components analysis), and outcomes of HIV risk reduction and social transformation. RESULTS: In multivariate analysis, we found that engagement with HIV programs and community mobilization activities was associated with the domains of empowerment. Power within and power with were positively associated with more program contact (p < .01 and p < .001 respectively). These measures of empowerment were also associated with outcomes of "personal transformation" in terms of self-efficacy for condom and health service use (p < .001). Collective empowerment (power with others) was most strongly associated with "social transformation" variables including higher autonomy and reduced violence and coercion, particularly in districts with programs of longer duration (p < .05). Condom use with clients was associated with power with others (p < .001), while power within was associated with more condom use with regular partners (p < .01) and higher service utilization (p < .05). CONCLUSION: These findings support the hypothesis that community mobilization has benefits for empowering FSWs both individually and collectively. HIV prevention is strengthened by improving their ability to address different psycho-social and community-level sources of their vulnerability. Future challenges include the need to develop social, political and legal contexts that support community mobilization of FSWs, and to prospectively measure the impact of combined community-level interventions on measures of empowerment as a means to HIV prevention.