India has been at the forefront of efforts to reduce maternal and child deaths, aligning its healthcare strategies with global commitments. In 2015, the nation adopted the Sustainable Development Goals (SDGs), committing to targeted interventions aimed at reducing maternal and child mortality through policy reforms, healthcare infrastructure advancements, and community-based programs [1]. In pursuit of these SDG goals, India launched the India Newborn Action Plan (INAP) in 2014, developed as a response to the global Every Newborn Action Plan (ENAP) [2]. The INAP aims to reduce preventable newborn deaths and stillbirths, contributing to a broader strategy for maternal mortality reduction. To achieve this, INAP is structured around six pillars of interventions, which include: Pre-conception and antenatal care, Care during labour and childbirth, Immediate newborn care, Care of healthy newborns, Care of small and sick newborns, Care beyond newborn survival [2].

Although these initiatives are scattered under various programs, maternal and child health challenges persist, particularly in rural India, where healthcare accessibility remains limited. According to the Sample Registration System (SRS) 2022 records, India’s Maternal Mortality Ratio (MMR) is 97 per 100,000 live births, while Neonatal Mortality Rate (NMR), Infant Mortality Rate (IMR), and Under-5 Mortality Rate (U5MR) stand at 20, 28, and 32 per 1,000 live births, respectively [3]. On the other hand, Stillbirth rates (SBR) for India show inconsistencies across data sources- SRS reports 3 per 1,000 births, Health Management Information System (HMIS) reports 12.4 per 1,000 births, and the National Family Health Survey-5 (NFHS-5) reports 9.7 per 1,000 births [4].

Despite maternal and child health programs focusing on maternal, neonatal and infant mortality, stillbirth prevention remains overlooked, even though evidence suggests that half of all stillbirths are preventable [5]. These deaths are largely attributed to sub-optimal healthcare systems in LMICs, necessitating improvements under the National Rural Health Mission (NRHM) to enhance maternal care delivery [6]. Additional challenges, such as low program reach, inconsistent implementation, and socio-cultural barriers, further hinder the effectiveness of maternal health interventions [7].

To comprehensively evaluate the effectiveness of maternal care programs in reducing stillbirths, this study employs the RE-AIM framework [8] by assessing service accessibility (Reach), intervention impact (Effectiveness), stakeholder uptake (Adoption), workforce and infrastructure challenges (Implementation), and long-term sustainability (Maintenance). We used RE-AIM for this analysis as it helps in systematically assessing programs.

This study is part of the formative phase of a larger multi-site, multi-phase implementation research, designed to develop an optimised model for maternal care interventions [4]. The qualitative approach allows exploration of barriers, facilitators, and program effectiveness in reducing stillbirth rates in tribal blocks of Pune district, contributing to policy recommendations for strengthening maternal healthcare delivery and achieving SDG targets for maternal and child health.

We used a rapid qualitative data analysis approach to code and analyse the data [10]. Adapted from traditional qualitative data analysis techniques, this is a recent approach that allows the extraction of important and focused results that can direct the planning and execution of interventions within a constrained timeframe [11]. The members of the study team (EC, NM, KK, SK and RP) who collected data coded respective audio recordings using a rapid analysis matrix. The matrix was created in Google Sheets using a deductive approach, which was accessible to all team members, whereby initial codes and the sub-codes were derived from the data collection tools, based on the WHO Health Systems framework. The team iteratively induced new codes in the matrix that surfaced from the data, in tune with the WHO Health Systems and RE-AIM framework. While coding the data from the audio recordings, the verbatim responses were directly translated and assigned to relevant codes and sub-codes. These codes and subcodes were then organised and mapped to the appropriate RE-AIM domains for analysis and interpretation of the summarised data.

Our study underscores persistent and critical gaps in maternal care service delivery across all RE-AIM dimensions, with particularly pronounced challenges among migrant and tribal populations. Consistent with earlier research, our findings reaffirm that socio-cultural, linguistic, and informational barriers remain central determinants of healthcare access in low- and middle-income countries (LMICs) [12]. Women from our study area frequently reported exclusion from government programmes due to lack of documentation, mistrust in public facilities, and language barriers—factors also identified in prior work exploring cultural beliefs and practices in Uganda, which highlighted the necessity of culturally sensitive interventions and sustained community engagement to improve perinatal outcomes [13].

In line with existing evidence from LMICs, healthcare access for our participants—particularly the beneficiaries from geographically remote or underserved communities—was hindered by scarcity of resources, both at the health system and patient level [14]. Our data revealed that misinformation and fear surrounding medical procedures, especially cesarean sections, added to delayed care-seeking, echoing findings from Haryana, where lack of prior facility identification, low awareness, and poor transport access during emergencies contributed to critical delays [15]. As a result, many women opted for private facilities, citing shorter wait times, greater availability, and perceived quality, despite the risk of fragmenting continuity of care and undermining public health interventions aimed at stillbirth reduction. Weak linkages between service providers and communities, limited community engagement, and the absence of trust-building activities remain key impediments to equitable reach [16].

Routine high-risk pregnancy (HRP) screenings in our study area were inconsistent, constrained by late pregnancy registration, unavailability of diagnostic tools for hypertension and gestational diabetes, and staff shortages. The WHO’s 2016 antenatal care guidelines emphasise the importance of early, risk-based screening to prevent adverse outcomes [17], yet implementation gaps are prominent. Cultural norms, such as antepartum restrictions [18] or delayed ANC visits and thus HRP detection, mirroring Singh et al.’s findings that resource-limited rural areas often lack the infrastructure for routine HRP monitoring [19]. In Karnataka, delayed disclosure of pregnancy has been shown to delay care initiation [20], underscoring the need for community-based approaches to promote early identification and enrolment in maternal care services.

Adoption of standardised MCH protocols varied widely across cadres and facility tiers in our study, with some CHWs and HCPs relying on “trial and error” in case management and demonstrating inconsistent definitions of stillbirth. These findings align with Sheikh et al., who emphasise that effective guideline uptake requires continued mentorship, context-specific local adaptation, and resource alignments for smooth functioning [21]. Limited awareness of official protocols among beneficiaries, coupled with high workloads among the healthcare workers, fragmented supervision, and inadequate visual protocols and IEC aids, further hindered consistent adoption. A study by Kawade et al., in 2021, from the same study area reiterates that ASHAs in India work up to 20 hours per week, balancing household responsibilities, other jobs, and health-related tasks, with tribal ASHAs facing additional challenges due to poor transport and remote locations [22]. ​Despite modest incentives and feelings of being rushed, they are proud of their role, motivated by community respect, and willing to take on new tasks, highlighting the need for improved recruitment, training, incentives, and policy adjustments to address their evolving role and sustain the program [22].​

Our findings demonstrate that even where guidelines exist, implementation fidelity was undermined by a lack of efficient training, motivated human resources, feedback mechanism, and weak referral pathways. Inadequate ambulance availability, especially at night, compounded access barriers similarly reported in Haryana [15] and other LMIC contexts [14]. Inefficient supply chains, frequent stock-outs of essential medicines (iron-folate, calcium, anti-D immunoglobulin), and maintenance lapses in equipment were also evident [23]. Digital health initiatives faced resistance from older staff, connectivity issues, and duplication of effort through parallel offline and online entries multiplies the barriers. Problems of inefficient referral loops, sometimes involving multiple facility transfers before delivery, are similar to what was found in Bangladesh, where timely complication detection and rapid referral have also shown to save maternal and neonatal lives [24].

While initial momentum for MCH programmes was high, sustainability was constrained by irregular training, lack of performance feedback loops, and inadequate incentives for CHWs, similar to the sustainability framework, which advocates for continuous professional development, structured monitoring, and supportive supervision [25]. CHWs in our study reported being blamed for adverse outcomes, which risks demoralisation and burnout. Infrastructural gaps, restrained/insufficient funding, and the absence of quality improvement and feedback mechanisms further hinder long-term programme impact.

Reducing stillbirths in rural India requires a multifaceted, sustainable approach to strengthen maternal care. Our qualitative study reveals persistent gaps across RE-AIM domains, especially among tribal and migrant beneficiaries. Addressing systemic, cultural, and infrastructural barriers is vital. Key strategies for addressing these challenges include culturally sensitive IEC and trust-building, early pregnancy identification and registration linked to subsidised diagnostics, standardised protocols with visual aids and referral algorithms, and public-private partnerships for care delivery. Strengthening supply chains, updating training materials, retraining CHWs and HCPs, and improving digital health records are also essential. Bridging these gaps can advance equitable, effective maternal care and reduce preventable stillbirths in similar LMIC settings.