Can we prevent stillbirths in India: A mixed-methods multisite study assessing Intrapartum care and public health facilities

Can we prevent stillbirths in India: A mixed-methods multisite study assessing Intrapartum care and public health facilities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Can we prevent stillbirths in India: A mixed-methods multisite study assessing Intrapartum care and public health facilities Kiran Kadam, Girish Dayma, Barsha Gadapani-Pathak, Suresh Yadav, and 18 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8336003/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 25 You are reading this latest preprint version Abstract Background: In India, stillbirth is still a significant, avoidable pregnancy outcome that reflects ongoing deficiencies in the standard of care for expectant mothers and newborns. Even though institutional deliveries have improved, a significant percentage of stillbirths happen during the intrapartum phase, frequently as a result of poor monitoring, a failure to recognize complications promptly, and a lack of facility readiness. This study aimed to assess the quality of intrapartum care and facility readiness across four diverse rural districts in India, identify key systemic and contextual challenges, and inform improvement strategies for reducing stillbirths. Methods: In the formative phase of an implementation research project, we carried out a sequential mixed-methods study. Direct, non-participating observations of 159 labouring women and readiness evaluations of 134 public health facilities comprised the quantitative component. Focus groups and in-depth interviews with healthcare professionals and community stakeholders were used to gather qualitative data. Descriptive statistics and thematic analysis were used to triangulate the data. Results: Adherence to evidence-based intrapartum care practices varied significantly between sites. Assessments of fetal heart sound and blood pressure were among the indicators that were not consistently monitored. Real-time documentation was frequently lacking, and partograph use was generally low. Procedures for administering oxytocin and handling emergencies varied. Assessments of facility preparedness showed that while basic newborn supplies and necessary medications were typically available, there was a lack of access to specialists, blood transfusion services, and sophisticated monitoring equipment (such as CTG). According to qualitative findings, multitasking, excessive workloads, and staff shortages are the main obstacles in providing quality care. Conclusion: Despite high rates of institutional births, rural India's lack of adequate intrapartum care and facility preparedness impedes efforts to lower the number of stillbirths. There is an urgent need for targeted interventions to improve real-time labor monitoring, increase workforce capacity, and deliver comprehensive emergency obstetric care. To meet national stillbirth reduction targets, strategies for implementing data-driven audits and embedding quality improvement cycles are essential. Keywords: Emergency obstetric care, Facility readiness, Health system, Intrapartum care, Maternal health, Mixed-methods, Rural India, Stillbirth prevention. Emergency obstetric care Facility readiness Health system Intrapartum care Maternal health Mixed-methods Rural India Stillbirth prevention Figures Figure 1 Figure 2 Figure 3 Introduction Stillbirth remains one of the most tragic and preventable adverse outcomes of pregnancy, reflecting persistent inequities in access to and quality of maternal and newborn healthcare ( 1 – 3 ). According to the World Health Organization (WHO), stillbirth is defined as the birth of a foetus with no signs of life at or beyond 28 weeks of gestation or weighing ≥ 1000 grams ( 2 ). The stillbirth rate (SBR) serves as a sensitive marker of the effectiveness, responsiveness, and quality of obstetric and perinatal health systems ( 3 ). The emotional and psychological impact of stillbirth extends beyond families to healthcare providers, making it both a clinical and social concern ( 4 ). In India, despite significant investments in maternal and newborn health programmes, stillbirth continues to pose a major public health challenge. The Health Management Information System (2019–20) reports an SBR of 12.4 per 1,000 births ( 5 ), while the National Family Health Survey-5 indicates a slightly lower rate of 9.7 per 1,000 births ( 6 ). A considerable proportion of these stillbirths occur during the intrapartum period due to preventable complications such as prolonged or obstructed labour, fetal distress, and umbilical cord accidents ( 7 , 8 , 9 ). These events often stem from suboptimal intrapartum monitoring, delayed recognition of maternal and fetal risk, and inadequate facility preparedness ( 10 , 11 , 12 ). Despite national initiatives such as the Pradhan Mantri Surakshit Matritva Abhiyan (PMSMA), the LaQshya Programme, and the India Newborn Action Plan that have improved institutional deliveries and skilled birth attendance ( 13 – 15 ), variations persist in the quality of intrapartum care and emergency response capacity across rural and resource-limited settings ( 16 – 17 ). Global and national evidence emphasize that strengthening intrapartum monitoring, ensuring timely access to comprehensive emergency obstetric care (CEmONC), and enhancing provider competence are critical for reducing preventable stillbirths ( 18 ). Against this background, the present study aims to assess the quality of intrapartum care and facility readiness across rural districts in India, as part of a larger implementation research study to address the gaps in quality of care and system preparedness. This study seeks to contribute to India’s progress toward achieving the Sustainable Development Goal (SDG) target of ending preventable stillbirths by 2030 ( 13 , 18 , 19 ). Methods Study setting: This study was undertaken as part of an implementation research project - SHRiSTI which aim to develop a comprehensive and replicable model for stillbirth reduction in India. Study was undertaken in four selected districts from across India covering a total of ~ 5.76 million population (Fig. 1 ) ( 19 ). For both the qualitative and quantitative components the study was undertaken at the selected healthcare facilities (Table 1 ). Table 1 Description of study Study site (District, State) Study Area (No. of blocks) Population in study area (in Lakhs) Number of Health care facilities within study area Tertiary care facilities First referral units Primary care facilities Palwal, Haryana 5 10.0 1 DH; 1 SDH 5 CHC 64 HWC; 19 PHC Sangrur, Punjab 4 10.45 1 DH; 3 SDH 6 CHC; 1 FRU 3 UPHC; 6 PHC; 16 Mini PHC; 162 HWC; 51 SHC Pune, Maharashtra 3 10.85 1 SDH 6 RH 35 PHC Udaipur, Rajasthan 3 7.98 2 SDH 8 CHC 23 PHC; 135 HWC Note: DH: District Hospital; SDH: Sub district hospital; CHC: Community Health Centres; HWC: Health and Wellness centre; PHC: Primary Health centres; FRU: First referral unit. Study Design The study employed sequential mixed methods design during the formative stage of implementation research. A quantitative observational study was undertaken, along with a qualitative phenomenological approach to explore, contextualize, and address gaps identified in the quantitative findings. We have adopted the GRAMMS checklist for reporting mixed-methods findings [20–22]. Quantitative component: The quantitative assessment included two components: Direct observation of institutional deliveries Direct observation of institutional deliveries from the point of admission to facility till birth of the baby to assess intrapartum care practices, including routine labour management and comprehensive emergency obstetric care. Observation of deliveries included women admitted in the latent or active stage of labour. Women with any complications were excluded from observation. No interventions were made at any stage — either before or during the observation of labour care practices; however, based on the observation, site-specific intervention packages were developed for testing and scaling at later stages. Assessment of facilities for readiness to deliver intrapartum services Facility assessment included data collection on human resources, infrastructure, equipment and medicines available for intrapartum care. The facilities were purposively selected to represent both high- and low-delivery-load settings. The assessment tool was prepared using the Indian Public Health Standards (IPHS) which outline the minimum benchmarks for infrastructure, human resources, equipment, and service delivery across public healthcare facilities in India, and the LaQshya guidelines which provide specific quality improvement protocols aimed at enhancing the standards of care in labour rooms and maternity operation theatres. Every study site recorded a minimum of thirty institutional births. Trained research personnel gathered observational data using standardized, pre-tested techniques that were integrated into RedCap and an Excel sheet. Newborn care, emergency obstetric care, labour management, and clinical protocol use were all recorded by the study tools. Qualitative component: In-depth interviews (IDIs) and focus group discussions (FGDs) were conducted till saturation of data was achieved. The study tools were designed specifically to interview Medical Officers, Staff Nurses, District Health Authorities, Pregnant women, and community stakeholders and were not published anywhere (Table 2 ). We used the Consolidated Framework of Implementation Research (CFIR) and WHO Health System Strengthening Framework as an overarching framework to guide the qualitative data collection and analysis. These guides were pretested and adapted to the local context across the study sites. The English version of the interview guides is provided as Supplementary File 1. Through this approach we intended to address gaps identified in the quantitative findings. We explored how individuals elucidate particular phenomenon like induction/ augmentation of labour in non-indicated cases from their own perspective. Table 2 Qualitative tools and participants interviewed, and preliminary themes explored Tool Pregnant women Doctors Nurses District health authorities Community (Husband, family members, Important/influential people in community) In-depth interview To explore their knowledge regarding practices and around intrapartum care. Obtain insights into the barriers and facilitators in practicing recommended care during delivery. -Understand the barriers and facilitators of providing care and implementation of government programs during intrapartum care. - Current status of implementation of the existing policies, programs and guidelines, challenges, and possible mitigation strategies for effective delivery of interventions. - Bottlenecks of implementation of various national programs targeted to improve birth outcomes. - Mitigation strategies and willingness to support the implementation research. Understand their awareness, knowledge and perceptions regarding care around childbirth; the government programs and schemes; barriers and facilitators in effective implementation, and possible mitigation strategies. Focus group discussion To explore their experiences around intrapartum care, including birth preparedness and reaching the health facility for delivery. Obtain insights into the barriers and facilitators in practicing recommended care during delivery. Understand their awareness, knowledge and perceptions regarding care around childbirth; the government programs and schemes; barriers and facilitators in effective implementation and possible mitigation strategies Data quality assurance: Consistency between sites was guaranteed by regular training and uniform, pre-tested tools. Data were frequently verified for quality and completeness and electronically confirmed in RedCap. Experienced researchers performed qualitative interviews, which were then audio recorded with consent and verified for accuracy. Statistical analysis: Quantitative data has been summarised in frequencies and percentages. All sites conducted deductive coding of the qualitative data followed by inducing new and important codes during the analysis. Rapid analysis and coding were conducted for data obtained from qualitative interviews. The interviews were transcribed verbatim and translated into English for thematic analysis. Codes were assigned to relevant excerpts of data guided by the gaps in quantitative findings. Themes and sub-themes were generated to explain these gaps. Key findings of the study were presented through quantitative analysis supplemented by verbatims to support the qualitative insights. Ethical considerations: Institutional ethics committees at each site provided their ethical approvals. At the district and facility levels, administrative approvals were obtained. All participants provided written informed consent, which included permission for audio recording. Throughout the study, data security and confidentiality were ensured ( 23 ). Results Data for this study were collected from four rural implementation sites—Palwal, Sangrur, Pune, and Udaipur. Intrapartum care practices were assessed through direct, non-participant observation of 159 women admitted for delivery, while 143 government health facilities were evaluated for their readiness to provide routine and emergency maternal and newborn services. Observational data focused on critical labour room practices, whereas facility assessments examined the availability of human resources, infrastructure, essential equipment, and drugs. Findings revealed substantial variation across sites in adherence to recommended practices during admission, labour monitoring, delivery, and immediate newborn care. Intrapartum Care Observations We have presented the findings in four stages based on Intrapartum care and delivery processes. On Admission: Effective intrapartum monitoring is central to preventing stillbirths, particularly through timely detection of maternal complications and fetal distress. However, our findings show wide variability across sites in the coverage and quality of monitoring practices. Blood pressure on admission was recorded for the majority of women in Udaipur (86.1%) and Sangrur (81.8%), followed by Palwal (58.0%), but rarely in Pune (10.0%). Qualitative data from Pune and Palwal site reported incomplete adherence to referral protocols when pregnancy-induced hypertension was identified which suggesting the moderate coverage of BP checks, but also highlighting gaps in follow-up care. Poor documentation was observed at Pune site. Fetal heart sound (FHS) assessment was universal in Sangrur (100%), higher in Pune (96%) followed by Palwal (78.0%), but much lower in Udaipur (36.1%). The inconsistent application of this basic monitoring parameter suggests a missed opportunity to identify intrapartum complications. Further, cervical dilatation was assessed in over 70% of women in all sites with Pune (87.5%) being the highest. Monitoring of uterine contractions was common in Pune (75.0%) and Udaipur (86.1%) whereas not in Palwal. In case of Sangrur site the initial assessment of pregnant women arriving at the facility for delivery was found to be timely and covered all parameters with, at least a third of the women being identified as high-risk at the time of delivery. While this indicates the robustness of initial assessment, it also highlight’s the missed opportunity for management of HRPs during the antenatal care. The qualitative insights from Staff nurses of DH, SDH and CHCs with delivery facility, highlighted systemic challenges at this stage. They suggest that the gaps in implementation at this stage was primarily due to the multiple responsibilities handled by limited number of staff nurses (SNs) managing the both labour room and ANC duties with minimal support from the medical officers. “We try to manage the emergency cases but if it’s not manageable then we refer the cases and sometimes we also refer the patient due unavailability of the staff ~ Palwal [Emergency pateint ko apne according manage karte hai, agar nahi hota refer karti hain, ya fir staff nhi to to pateint ko refer kar dete hain, CHC me 5 female staff nurses to chahiye hi par yha 4 hai”] Labor Monitoring: Our data on labour monitoring also showed inconsistent adherence to recommended practices. Per-vaginal (PV) examinations were conducted in 72.5% of women in Pune and 75.8% in Sangrur, but lower in Udaipur (50.0%). Artificial rupture of membranes (ARM) was frequent in Palwal (48%), but rare elsewhere (< 15%). Limited medical officer involvement and high workload among staff nurses contributed to unsupervised use of ARM and focus on third-stage oxytocin to prevent postpartum haemorrhage. Partograph initiation was limited across all sites, highest in Sangrur (24.2%). Partograph review prior to delivery was negligible across sites (< 35%), with zero use in Palwal and Pune, nonetheless qualitative data from Pune reported retrospective documentation of partograph. Overload and task shifting, with ANMs often assisting in labour without adequate supervision by medical officers was one of key reasons highlighted from the qualitative insights. This also led to missed routine checks like BP or FHR and it’s documentation. In Sangrur, real time partograph use was scarce and interaction with labour room staff reiterated manpower shortage and case load. Even though staff were available on call, frontline shortage and high workload reduced the quality of monitoring. Ongoing FHS monitoring was consistently high in Sangrur (100%) and Palwal (78%), but substantially lower in Udaipur (36.1%) and Pune (57.5%). Oxytocin use in the first stage of labour was rare across all sites (< 15%). Second-stage oxytocin use was high in Sangrur (75.8%), Pune reported it for 57.5%, while third-stage use was most common only in Palwal (66%). The in-depth interviews with ANMs suggests that cultural/familial pressure for “faster delivery/ outcome to reduce the suffering of the pregnant women” contributed to inappropriate oxytocin administration shortages of trained staff and fear of complications, which often may lead to a preference for caesarean delivery or early oxytocin use. In Udaipur, restrictive protocols prevented peripheral staff from administering oxytocin in early labour, explaining low uptake. “We try to fill it (partograph) in real time but sometimes when there is patient load it becomes difficult as I am the only staff nurse in the department” ~Sangrur “They do not have the machine to check FHS. It has been in use recently; it was not there at the hospital earlier.” ~ Pune “We refer most cases which are primi or for LSCS. Madam was there earlier, we would still do primi cases but now we are doing 2nd gravida, third gravida which come dilated, 5–6 fingers” ~ Sangrur Delivery Care & Newborn Care: Intrapartum oxytocin use (any stage) was highest in Palwal (84.0%) followed by Sangrur (75.8%), but was negligible in Pune (2.5%) and absent in Udaipur. Antibiotic use was highest in Sangrur (45.5%), but rare elsewhere (< 5%). Referrals from labour rooms were infrequent overall, except in Pune (22.5%). Staff nurses often lacked confidence in neonatal resuscitation and preferred immediate referral from lower-level facilities due to the absence of a paediatricians across all sites. In Udaipur, lower-level facilities restricted themselves to normal deliveries, with complicated cases routinely referred. Documentation of foetal distress was low across all sites (6.0% in Palwal; 12.1% in Sangrur and Udaipur). Resuscitation was most frequent in Sangrur (27.3%) compared to 8–8.3% in rest of other sites. Across all deliveries, oxygen support was required by 22.2% of newborns in Udaipur and 12.1% in Sangrur, highlighting variability in immediate newborn care needs(Table 3 ). “We give 5 units (1 ampule) by drip for inducing contractions after 5–6 cm dilatation, which we also confirm using 3 fingers.” ~Sangrur “There is also a need for more child doctors at the municipal hospital since most people like us who face financial hardships are referred there. So, government must ensure the availability of doctors. They do not have enough services to offer to patients like me. A pediatrician should be available there. ~ Pune “High risk cases like CPD, hypertension, twins are usually referred to higher facility after giving first line of treatment as doctors are not available round the clock [High risk wale case ko ye normally refer hi karte hai jaise CPD, leaking aur koi hypertension hai, twins’ pregnancy hai to first treatment dekar higher facility me refer karti hai, kyoki yaha par 24 hours ke liye doctors nahi hai].” ~Palwal Table 3 Assessment of Intrapartum care Indicators by Site Indicators Palwal (n = 50) Sangrur (n = 33) Udaipur (n = 36) Pune (n = 40) 1. On Admission Women whose Blood pressure measurement done 29(58%) 27(81.8%) 31(86.1%) 4(10%) Women whose Foetal heart sound measurement done 39(78%) 33(100%) 13(36.1%) 36(90%) Women whose Cervical Dilatation measurement done 27(54%) 25(75.8%) 26(72.2%) 35(87.5%) Women whose Uterine Contraction measurement done 0 22(66.7%) 31(86.1%) 30(75%) Women whose partograph reviewed before delivery 0 11(33.3%) 2(5.6%) 0 2. Labour Monitoring PV examinations done 27(54%) 25(75.8%) 18(50%) 29(72.5%) Artificial rupture of membranes performed 24 (48%) 5(15.2%) 0 0 Partograph initiated 0 8(24.2%) 2(5.6%) 2(5%) Women whose Foetal heart sound measurement done 39(78%) 33(100%) 13(36.1%) 23(57.5%) Women whose Cervical Dilatation measurement done 27(54%) 19(57.6%) 26(72.2%) 25(62.5%) Women whose Uterine Contraction measurement done 50(100%) 22(66.7%) 31(86.1%) 16(40%) Women administered with oxytocin during 1st stage of labour 2(4%) 5 (15.2%) 1(2.8%) 2(5%) Women administered with oxytocin during 2nd Stage of Labour 7(14%) 25(75.8%) 0 23(57.5%) Women administered with oxytocin during 3rd Stage of labour (AMTSL) 33(66%) 3(9.1%) 0 1(2.5%) 3. Delivery care Intrapartum use of oxytocin, 42(84%) 25(75.8%) 0 1(2.5%) Intrapartum antibiotics 1(2%) 15(45.5%) 0 03(7.5%) No. of Cases referred from the labour room 0 5 (15.2%) 3(8.3%) 9(22.5%) 4. New born care Foetal distress documented 1(2%) 0 0 3(7.5%) Resuscitation 1(2%) 9(27.3%) 3(8.3%) 3(7.5%) Oxygen support 1(2%) 4(12.1%) 8(22.2%) 3(7.5%) Findings indicate notable site-level disparities, particularly in admission assessments, partograph use, and oxytocin administration practices. Sangrur showed higher coverage for several monitoring indicators, while Palwal had higher third stage oxytocin use. Udaipur demonstrated stronger uterine contraction monitoring but lagged in other intrapartum indicators. Pune underperformed in admission assessments but reported higher second stage oxytocin use and referral rate. These findings collectively suggest that even where basic monitoring is taking place, emergency protocols are either not being implemented or are inconsistently followed. The low adherence to life-saving interventions reflects systemic issues related to staff competency, workload, supervision, and availability of essential supplies. (Fig. 2). Interpretation of Facility Assessment A total of 143 facilities were assessed across four sites (Palwal, Sangrur, Udaipur, and Pune) provision of quality intrapartum and newborn care. 88 facilities included district hospitals, sub-district hospitals, rural hospitals, and primary health centres and remaining facilities were sub-centres. Table 4 Availability of Essential Newborn Care equipment by sites Facility readiness indicators Palwal (n = 17) Sangrur (n = 20) Udaipur (n = 32) Pune (n = 19) Newborn resuscitation corner with functional radiant warmer 16 (94.1%) 10 (50%) 15(46.9%) 15 (78.9%) Suction apparatus 16 (94.1%) 11 (55%) 18 (56.3%) 19 (100%) Neonatal bag and masks 16 (94.1%) 11(55%) 16 (50%) 19 (100%) Blood transfusion or blood products 2 (11.80%) 4 (20%) 2 (6.3%) 10 (52.6%) Functional cardiotocography 0 1 (5%) 8 (25%) 11(57.9%) No. of facilities having antenatal corticosteroids 17(100%) 10 (50%) 30 (93.8%) 14 (73.7%) No. of facilities having Methergine 14 (82.40%) 11(55%) 18 (56.3%) 13 (68.4%) No. of facilities in which medical officer available 24*7 to attend to women in labour or the baby at birth 4 (23.50%) 12 (60%) 14 (43.8%) 16 (84.2%) No. of facilities having triage area for pregnant women 7 (41.20%) 13 (65%) 10 (31.3%) 8 (42.1%) No. of facilities having ambulance available 24*7 12(76.60%) 14 (70%) 13 (40.6%) 19 (100%) No. of facilities having oxygen central supply/concentrators/cylinders 16 (94.1%) 15 (75%) 22 (68.8%) 19 (100%) No. of facilities having functional foetal doppler 17 (100%) 16 (80%) 11 (34.4%) 19 (100%) Essential Newborn Care Equipment: Most facilities were equipped with a newborn resuscitation corner with a functional radiant warmer in Palwal (94.1%), Udaipur (46.9%), Pune (78.9%), and Sangrur (90.9%). Functional suction apparatus and appropriately sized neonatal bag and masks were available in more than 85% of facilities in Palwal, Udaipur, and Pune, but in 81.8% of Sangrur facilities Critical Maternal and Newborn Care Supplies: Availability of oxytocin was high in Palwal (94.1%) and Udaipur (87.5%) but lower in Sangrur (50.0%). Antenatal corticosteroids were present in all facilities in Palwal (100%) followed by Udaipur (93.8%) and facilities in Sangrur with delivery points had 100% oxytocin use. Methergine availability was moderate across sites (Palwal 82.4%, Sangrur 55.0%, Udaipur 56.3%, Pune 68.4%). Advanced Monitoring and Blood Products: Blood transfusion or blood product availability was limited in all sites except Pune (52.6%). Functional cardiotocography (CTG) was absent in Palwal, rare in Sangrur (9.1%), but higher in Udaipur (25.0%) and Pune (57.9%). Human Resources and Triage: Twenty-four-hour availability of a medical officer for labour and newborn care was highest in Pune (84.2%) and Udaipur (43.8%), but limited in Palwal (23.5%). Triage areas for pregnant women were most common in Sangrur (65.0%), but less frequent in Pune (42.1%) and Palwal (41.2%). Transport and Oxygen Supply: Ambulance availability round-the-clock was highest in Pune (100%) and Sangrur (70.0%), and lower in Palwal (70.6%). Central oxygen supply, concentrators, or cylinders were available in most facilities in Palwal (94.1%), Udaipur (68.8%), and Pune (100%), but less so in Sangrur (75.0%). Foetal Monitoring Devices: Functional foetal dopplers were available in all Palwal facilities (100%), most Sangrur (80.0%) and Pune (100%), but in only 34.4% of Udaipur facilities. Facility readiness varied widely between and within states. While basic newborn resuscitation equipment and essential drugs were generally available, gaps persisted in advanced monitoring capabilities, blood product availability, and consistent 24×7 staffing, particularly in Palwal and Sangrur. Pune facilities demonstrated relatively better readiness in emergency transport, oxygen supply, and CTG availability. (Table 4 ). Table 5 Availability of Critical Maternal and Newborn Drugs and Supplies by sites Facility readiness indicators Palwal (n = 24) Sangrur (n = 40) Udaipur (n = 50) Pune (n = 29) Facilities having anticonvulsants 2(8.3%) 10(25%) 23 (46%) 13 (44.8%) Facilities having antihypertensive (injectable/ tablets) 14 (58.3%) 21(52.5%) 31(62%) 22 (75.9%) Anticonvulsants were available in less than half of facilities in all sites, with highest availability in Udaipur (46.0%) and Pune (44.8%), and lowest in Palwal (8.3%). Antihypertensives (injectable/tablets) were more widely available, ranging from 52.5% in Sangrur to 75.9% in Pune. (Table 5 ). Across the four study sites, availability of key specialists and essential services varied considerably. Table 6 Advanced Monitoring, Blood Products, and Infrastructure Readiness by sites Facility readiness indicators Palwal (n = 7) Sangrur (n = 10) Udaipur (n = 13) Pune (n = 7) Facilities in which obstetrician available on call 2(28.6%) 5(50%) 6(46.2%) 7(100%) Facilities in which paediatrician available on call 1(14.3%) 2(20%) 4(30.8%) 6(85.7%) Facilities having Anaesthetists on call or Medical Officer trained in Anaesthesia available 1(14.3%) 2(20%) 2(15.4%) 5(71.4%) Facilities having Blood bank/ blood storage facilities 1(14.3%) 1(10%) 2(15.4%) 1(14.3%) Facilities having functional ultrasound 24*7 0 2(20%) 7(53.8%) 0 Availability of key specialists and critical services varied considerably across study sites. Pune demonstrated the highest readiness, with all facilities (100%, 7/7) consistently having an obstetrician on call, followed by Sangrur (50%, 5/10), Udaipur (46.2%, 6/13), and Palwal (28.6%, 2/7). Paediatricians were most frequently available in Pune (85.7%, 6/7), with substantially lower proportions in Udaipur (30.8%, 4/13), Sangrur (20%, 2/10), and Palwal (14.3%, 1/7). The presence of an anaesthetist or trained medical officer for emergency obstetric care mirrored this trend, with Pune again leading (71.4%, 5/7) and much lower availability in Sangrur and Udaipur (each 20% and 15.4%, respectively) and Palwal (14.3%, 1/7). Access to blood bank or blood storage facilities was limited across all districts, found only in Udaipur (15.4%, 2/13), Sangrur (10%, 1/10), Pune (14.3%, 1/7), and Palwal (14.3%, 1/7). Regarding diagnostic capacity, functional 24×7 ultrasound services were identified most frequently in Udaipur (53.8%, 7/13), followed by Sangrur (20%, 2/10), with no such service available in facilities surveyed in Palwal or Pune. (Table 6 ). This highlights persistent gaps in the availability of specialist staff and essential support services for comprehensive emergency obstetric and newborn care. Qualitative findings for facility assessment Across sites, facility assessment revealed a partial adequacy. While most facilities had basic infrastructure, essential drugs, and neonatal resuscitation equipment, advanced readiness indicators such as functional blood banks, cardiotocography, round-the-clock specialist coverage, and reliable referral systems were lacking. Palwal and Sangrur were particularly constrained by human resource shortages, with limited numbers of staff nurses and poor availability of specialists, leading to heavy multitasking and compromised emergency response. Udaipur demonstrated relatively good availability of essential drugs and oxygen support, yet had serious deficiencies in blood storage, CTG, and specialist coverage, compounded by weak infrastructure and geographic barriers. Pune performed better on most readiness indicators, with higher specialist availability, oxygen supply, and ambulance services, but still faced frontline staff shortages and dependency on referral systems for complications. Taken together, the findings indicate that although routine delivery care is feasible at most facilities, the capacity to provide comprehensive emergency obstetric and newborn care (CEmONC) is inadequate across all sites, limiting the ability to manage complications in a timely and effective manner. “In the government facility, there was a waiting period of 1 to 1 and a half month for sonography.” (Pune) “No ambulance services were available. We had to arrange our vehicle for transport to the municipality hospital” (Pune) This variation highlights critical service gaps, especially in paediatric coverage, anaesthesia services, and round-the-clock ultrasound availability. These gaps are particularly concerning given that all sites were implementing partners under the stillbirth reduction initiative. The findings suggest that existing programmatic efforts have yet to translate into consistent, high-quality service delivery, highlighting a disconnect between policy intent and ground-level implementation. The interpretation of observed practices and facility assessments clearly demonstrates that both routine monitoring and emergency readiness for intrapartum care are insufficient across all sites. While a few elements, such as FHS monitoring and cervical checks, show moderate coverage, core practices like partograph usage and emergency interventions are nearly absent. (Fig. 3). Facility limitations in skilled human resources, essential equipment, and emergency drugs mirror these clinical gaps and likely contribute to substandard outcomes. These findings indicate an urgent need for strategic intervention targeting health worker training, resource allocation, and supervision to improve adherence to evidence-based intrapartum care practices. Discussion The quality of intrapartum treatment and facility preparedness varied significantly among India's rural districts, according to this multisite review. Complete intrapartum care guidelines were not always followed, even if several critical monitoring procedures, such as blood pressure checks and foetal heart sound (FHS) evaluations, were carried out regularly at a few clinics. Retrospective entries frequently replaced the place of real-time documentation, and partograph utilization remained remarkably low. Practices for administering oxytocin also differed; delays or improper use suggested a lack of oversight and inconsistent provider skill. These results were supported by qualitative insights, which showed that multitasking, excessive workload, and insufficient personnel were the primary barriers to successful intrapartum surveillance. Facility readiness assessments discovered that most facilities had the basic medicines and baby care tools. But they were still significantly short of experts, blood transfusion services, and novel monitoring tools like cardiotocography (CTG). Pune demonstrated relatively better readiness and adherence compared to Palwal and Sangrur, where systemic challenges were more prominent. These findings underline the gap between national program expectations and ground-level implementation of evidence-based intrapartum practices. Our findings are in accordance with past studies from India and other LMICs that demonstrated inadequate facility readiness and poor adherence to intrapartum care guidelines. Numerous studies conducted in various Indian states have documented low partograph use and insufficient foetal monitoring during labour, which directly contribute to preventable stillbirths and neonatal morbidity ( 24 – 26 ). Regular foetal heart monitoring and labour audits, for instance, were linked to a 59% decrease in intrapartum stillbirths over time, despite the fact that only 8.7% of labour cases used partographs, according to a multisite surveillance study from North India ( 24 ). Similarly, a facility-based assessment in aspirational districts of Jharkhand, Odisha, and Uttarakhand revealed that foetal heart rate (FHR) monitoring was often done only once during labour, with minimal monitoring during the second stage, leading to missed opportunities for timely intervention ( 25 ). These trends are supported by comparable data from other LMICs. According to an Ethiopian study, the odds of stillbirth were 80% lower for women whose labour was tracked with a partograph than for those who did not ( 27 ). Prolonged labour, substandard foetal monitoring, and infrequent ANC visits were found to be important factors in stillbirth in another Ethiopian study ( 28 ). All of these studies support the idea that, in settings with limited resources, one of the most prevalent causes of stillbirth is inadequate intrapartum monitoring, especially the failure to recognize and address foetal distress. Evaluations of India's LaQshya and PMSMA programs also support our findings, demonstrating that states with more robust oversight, frequent audits, and provider mentoring have higher compliance rates with quality-of-care standards ( 29 , 30 ). However, as the SHRiSTI project highlighted, frontline staff frequently deal with a heavy caseload, conflicting programmatic demands, and a lack of supportive supervision, all of which make it difficult to consistently follow intrapartum protocols ( 31 , 32 ). This study confirms that quality deficiencies, not coverage gaps, are the cause of India's ongoing intrapartum stillbirth burden. Even though institutional deliveries are common, many facilities lack the procedures, knowledge, and accountability frameworks required to guarantee safe childbirth. Improving results requires enhancing real-time monitoring procedures, particularly making sure that partograph use becomes a regular, supervised activity. Promising outcomes concerning improving protocol adherence and early foetal distress detection have been demonstrated by digital labour monitoring tools and feedback-based audit mechanisms ( 33 ). The lack of human resources at all levels highlights the necessity of skill-based capacity building, supportive supervision, and task-sharing techniques. When integrated into mentorship programs, regular simulation-based training for obstetric emergencies may boost provider confidence and minimize clinical errors. For timely management of complications, it is crucial to guarantee 24-hour access to Comprehensive Emergency Obstetric and Newborn Care (CEmONC) services, including blood transfusion and specialist availability. More uniformity in implementation can be achieved at the policy level by coordinating current national programs with WHO's Quality of Care for Maternal and Newborn Health Standards. Accountability and evidence-based action would be encouraged by establishing regular quality audits, reviewing maternal and perinatal deaths, and connecting facility data to perinatal outcomes. Strengths and Limitations This study's mixed-methods approach, which combined qualitative insights, facility assessment, and direct observation, is one of its main strengths. This all-encompassing viewpoint made it possible to triangulate the evidence and find systemic and operational factors that contribute to subpar intrapartum quality. The findings are more broadly applicable due to the multisite coverage in four different settings. However, the possibility of observer bias (Hawthorne effect) cannot be excluded, as staff behaviour might have changed during observation. Assessments of the facilities were a cross-sectional snapshot and might not have taken into account changes in staffing or supply availability over time. The exclusion of private sector facilities restricts extrapolation to all settings for childbirth. The study does, however, provide important evidence regarding the ongoing intrapartum quality disparities that contribute to poor perinatal outcomes. Recommendations and Future Directions Strengthen intrapartum monitoring with digital tools, supportive supervision, as well as mandatory partograph audits. Increase the availability of human resources through rotation planning, task sharing, and ongoing skill-based training. Maintaining vital supplies, blood storage, and referral connections will help to ensure that the facility is prepared for emergency response. Establish regular labour room audits and stillbirth review committees to codify cycles of quality improvement. Facilitate ongoing learning and accountability, integrate data systems that connect perinatal outcomes with intrapartum practices. Future studies should assess how effectively structured quality improvement models, like mentorship-based LaQshya reinforcement and digital partographs, reduce intrapartum stillbirths and enhance maternal outcomes in all settings. Conclusion Despite India’s progress in institutional delivery, quality of intrapartum care continues to determine perinatal outcomes. Strengthening labour monitoring, building workforce capacity, and ensuring facility preparedness are essential to achieve Every Newborn Action Plan goal of ≤ 10 stillbirths per 1,000 births by 2035. Declarations Ethics approval and consent to participate The ethical approval for this study was obtained from KEM Hospital Research Centre Institutional Ethics Committee (Reference No. KEMHRC/RVM/EC/1964) for Pune site; Institutional Review Board, International Institute of Health Management Research Delhi (Ref no: IRB/2024-2025/01) for Sangrur site; ICMR-NIRNCD institutional ethics committee (Ref no: IEC-NIIRNCD/2023/DEC/FR/004) for Jodhpur site; and Society of Applied statistics Institutional Ethics committee (Ref No: SAS/ERC/ICMR Stillbirths Study/2024) . Administrative permissions were obtained at district and facility levels prior to data collection. The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants before data collection, including consent for audio recording of interviews. Confidentiality and data security were maintained throughout the study. Consent for publication Not Applicable Availability of data and materials The data will be made available on reasonable request. Competing interests All authors declare that they have no completing interest Funding This work was supported by the Indian Council of Medical Research (ICMR) [grant ID: 5/7/BMIPR/2022-RCN]. Authors’ Contribution RP, KK, GD, NA, BGP, SM, SK, SBN, RB, AKP, DG, VK, SM and RM jointly developed the study concept and design. RP, KK, NM, GD, NA, BGP, SM, SR and SB coordinated and supervised data collection across the participating sites. Data analysis and interpretation were carried out by RP, KK, NM, GD, AKP, RB and NA. The initial draft of the manuscript was prepared by RP, KK, NM, GD, AKP, DG, SK and RM. All authors—including MG, SD, IK, SY and other collaborators—contributed to reviewing and refining the manuscript and provided important intellectual input. Every author approved the final version of the manuscript and accepts responsibility for the accuracy and integrity of the work. Acknowledgment The authors acknowledge the contributions of Dr. Pranay Vats, Dr. Sonia Maurya, and Mr. Aditya Bhatt from research team (SAS) towards data generation and analysis, part of which has been incorporated in this manuscript. Additionally, Palwal research team is grateful to Mission Director National Health Mission Haryana, Director, Maternal and Child Health, NHM, Haryana and Chief Medical officer of Palwal district for their consistent support during implementation study at Haryana-site. We are grateful to the Indian Council of Medical Research (ICMR) for their support and the team from the State Health Systems Resource Centre (SHSRC), Pune for their technical assistance throughout the study. References Da Silva FT, Gonik B, McMillan M, Keech C, Dellicour S, Bhange S, et al. Stillbirth: Case definition and guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine. 2016;34(49):6057–68. Perinatal surveillance and prevention of birth defects. : Progress Review [Internet]. [cited 2025 Jul 23]. https://www.who.int/publications/i/item/se-cah-29 De Bernis L, Kinney MV, Stones W, Ten Hoope-Bender P, Vivio D, Leisher SH, et al. Stillbirths: ending preventable deaths by 2030. Lancet. 2016;387(10019):703–16. Bhutta ZA, Yakoob MY, Lawn JE, Rizvi A, Friberg IK, Weissman E, et al. Stillbirths: what difference can we make and at what cost? Lancet. 2011;377(9776):1523–38. Statistics, Division. 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Gopalakrishnan S, Sharma M, Ramesh B. Understanding workload and performance challenges among labour room staff in public facilities in India. Indian J Community Med. 2020;45(2):165–71. Srivastava A, Sharma N, Murthy GVS. Barriers to adherence with intrapartum care protocols among nurses in India: a qualitative study. BMC Health Serv Res. 2018;18:472. Moucheraud C, Worku A, Tesfaye M, et al. Improving quality of intrapartum care in low-resource settings through continuous monitoring and feedback. Reprod Health. 2019;16:163. Additional Declarations No competing interests reported. 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2","display":"","copyAsset":false,"role":"figure","size":81078,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eObserved Intrapartum Practices-Traffic -light Heat Map\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8336003/v1/2b6ddd2613bf8b435165e19c.png"},{"id":100363890,"identity":"18bd646e-bc05-4e9d-a1c5-e4e867f9ac37","added_by":"auto","created_at":"2026-01-16 07:51:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65612,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFacility Readiness- Heat Light Map\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8336003/v1/8a8883811327c39b964b3bb9.png"},{"id":100381911,"identity":"8f3f2bb7-5d8f-4494-bda0-e869c89960ec","added_by":"auto","created_at":"2026-01-16 10:39:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1728274,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8336003/v1/5381267d-dac3-4ee6-9b62-d39e590f2247.pdf"},{"id":100364392,"identity":"736f8cc7-805c-4a3c-923d-ddb45b5530f7","added_by":"auto","created_at":"2026-01-16 07:53:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":679205,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8336003/v1/2e963d3a1411b08d8e8cb772.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can we prevent stillbirths in India: A mixed-methods multisite study assessing Intrapartum care and public health facilities","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStillbirth remains one of the most tragic and preventable adverse outcomes of pregnancy, reflecting persistent inequities in access to and quality of maternal and newborn healthcare (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). According to the World Health Organization (WHO), stillbirth is defined as the birth of a foetus with no signs of life at or beyond 28 weeks of gestation or weighing\u0026thinsp;\u0026ge;\u0026thinsp;1000 grams (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The stillbirth rate (SBR) serves as a sensitive marker of the effectiveness, responsiveness, and quality of obstetric and perinatal health systems (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The emotional and psychological impact of stillbirth extends beyond families to healthcare providers, making it both a clinical and social concern (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn India, despite significant investments in maternal and newborn health programmes, stillbirth continues to pose a major public health challenge. The Health Management Information System (2019\u0026ndash;20) reports an SBR of 12.4 per 1,000 births (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), while the National Family Health Survey-5 indicates a slightly lower rate of 9.7 per 1,000 births (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). A considerable proportion of these stillbirths occur during the intrapartum period due to preventable complications such as prolonged or obstructed labour, fetal distress, and umbilical cord accidents (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These events often stem from suboptimal intrapartum monitoring, delayed recognition of maternal and fetal risk, and inadequate facility preparedness (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite national initiatives such as the Pradhan Mantri Surakshit Matritva Abhiyan (PMSMA), the LaQshya Programme, and the India Newborn Action Plan that have improved institutional deliveries and skilled birth attendance (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), variations persist in the quality of intrapartum care and emergency response capacity across rural and resource-limited settings (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Global and national evidence emphasize that strengthening intrapartum monitoring, ensuring timely access to comprehensive emergency obstetric care (CEmONC), and enhancing provider competence are critical for reducing preventable stillbirths (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Against this background, the present study aims to assess the quality of intrapartum care and facility readiness across rural districts in India, as part of a larger implementation research study to address the gaps in quality of care and system preparedness. This study seeks to contribute to India\u0026rsquo;s progress toward achieving the Sustainable Development Goal (SDG) target of ending preventable stillbirths by 2030 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy setting: This study was undertaken as part of an implementation research project - SHRiSTI which aim to develop a comprehensive and replicable model for stillbirth reduction in India. Study was undertaken in four selected districts from across India covering a total of ~\u0026thinsp;5.76\u0026nbsp;million population (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). For both the qualitative and quantitative components the study was undertaken at the selected healthcare facilities (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy site\u003c/p\u003e \u003cp\u003e(District, State)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy Area (No. of blocks)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePopulation in study area (in Lakhs)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eNumber of Health care facilities within study area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTertiary care facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFirst referral units\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePrimary care facilities\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalwal, Haryana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 DH; 1 SDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 CHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64 HWC; 19 PHC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSangrur, Punjab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 DH; 3 SDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 CHC; 1 FRU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 UPHC; 6 PHC; 16 Mini PHC; 162 HWC; 51 SHC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePune, Maharashtra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 SDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 RH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35 PHC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUdaipur, Rajasthan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 SDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 CHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 PHC; 135 HWC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: DH: District Hospital; SDH: Sub district hospital; CHC: Community Health Centres; HWC: Health and Wellness centre; PHC: Primary Health centres; FRU: First referral unit.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStudy Design\u003c/strong\u003e \u003cp\u003eThe study employed sequential mixed methods design during the formative stage of implementation research. A quantitative observational study was undertaken, along with a qualitative phenomenological approach to explore, contextualize, and address gaps identified in the quantitative findings. We have adopted the GRAMMS checklist for reporting mixed-methods findings [20\u0026ndash;22].\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative component:\u003c/h2\u003e \u003cp\u003eThe quantitative assessment included two components:\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDirect observation of institutional deliveries\u003c/h3\u003e\n\u003cp\u003eDirect observation of institutional deliveries from the point of admission to facility till birth of the baby to assess intrapartum care practices, including routine labour management and comprehensive emergency obstetric care. Observation of deliveries included women admitted in the latent or active stage of labour. Women with any complications were excluded from observation. No interventions were made at any stage \u0026mdash; either before or during the observation of labour care practices; however, based on the observation, site-specific intervention packages were developed for testing and scaling at later stages.\u003c/p\u003e\n\u003ch3\u003eAssessment of facilities for readiness to deliver intrapartum services\u003c/h3\u003e\n\u003cp\u003eFacility assessment included data collection on human resources, infrastructure, equipment and medicines available for intrapartum care. The facilities were purposively selected to represent both high- and low-delivery-load settings. The assessment tool was prepared using the Indian Public Health Standards (IPHS) which outline the minimum benchmarks for infrastructure, human resources, equipment, and service delivery across public healthcare facilities in India, and the LaQshya guidelines which provide specific quality improvement protocols aimed at enhancing the standards of care in labour rooms and maternity operation theatres.\u003c/p\u003e \u003cp\u003eEvery study site recorded a minimum of thirty institutional births. Trained research personnel gathered observational data using standardized, pre-tested techniques that were integrated into RedCap and an Excel sheet. Newborn care, emergency obstetric care, labour management, and clinical protocol use were all recorded by the study tools.\u003c/p\u003e\n\u003ch3\u003eQualitative component:\u003c/h3\u003e\n\u003cp\u003eIn-depth interviews (IDIs) and focus group discussions (FGDs) were conducted till saturation of data was achieved. The study tools were designed specifically to interview Medical Officers, Staff Nurses, District Health Authorities, Pregnant women, and community stakeholders and were not published anywhere (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We used the Consolidated Framework of Implementation Research (CFIR) and WHO Health System Strengthening Framework as an overarching framework to guide the qualitative data collection and analysis. These guides were pretested and adapted to the local context across the study sites. The English version of the interview guides is provided as \u003cb\u003eSupplementary File 1.\u003c/b\u003e Through this approach we intended to address gaps identified in the quantitative findings. We explored how individuals elucidate particular phenomenon like induction/ augmentation of labour in non-indicated cases from their own perspective.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQualitative tools and participants interviewed, and preliminary themes explored\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTool\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePregnant women\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDoctors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNurses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDistrict health authorities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCommunity\u003c/p\u003e \u003cp\u003e(Husband, family members, Important/influential people in community)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-depth interview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTo explore their knowledge regarding practices and around intrapartum care.\u003c/p\u003e \u003cp\u003eObtain insights into the barriers and facilitators in practicing recommended care during delivery.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e-Understand the barriers and facilitators of providing care and implementation of government programs during intrapartum care.\u003c/p\u003e \u003cp\u003e- Current status of implementation of the existing policies, programs and guidelines, challenges, and possible mitigation strategies for effective delivery of interventions.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e- Bottlenecks of implementation of various national programs targeted to improve birth outcomes.\u003c/p\u003e \u003cp\u003e- Mitigation strategies and willingness to support the implementation research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnderstand their awareness, knowledge and perceptions regarding care around childbirth; the government programs and schemes; barriers and facilitators in effective implementation, and possible mitigation strategies.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFocus group discussion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTo explore their experiences around intrapartum care, including birth preparedness and reaching the health facility for delivery.\u003c/p\u003e \u003cp\u003eObtain insights into the barriers and facilitators in practicing recommended care during delivery.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnderstand their awareness, knowledge and perceptions regarding care around childbirth; the government programs and schemes; barriers and facilitators in effective implementation and possible mitigation strategies\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData quality assurance:\u003c/h3\u003e\n\u003cp\u003eConsistency between sites was guaranteed by regular training and uniform, pre-tested tools. Data were frequently verified for quality and completeness and electronically confirmed in RedCap. Experienced researchers performed qualitative interviews, which were then audio recorded with consent and verified for accuracy.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eQuantitative data has been summarised in frequencies and percentages. All sites conducted deductive coding of the qualitative data followed by inducing new and important codes during the analysis. Rapid analysis and coding were conducted for data obtained from qualitative interviews. The interviews were transcribed verbatim and translated into English for thematic analysis. Codes were assigned to relevant excerpts of data guided by the gaps in quantitative findings. Themes and sub-themes were generated to explain these gaps. Key findings of the study were presented through quantitative analysis supplemented by verbatims to support the qualitative insights.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical considerations:\u003c/h3\u003e\n\u003cp\u003eInstitutional ethics committees at each site provided their ethical approvals. At the district and facility levels, administrative approvals were obtained. All participants provided written informed consent, which included permission for audio recording. Throughout the study, data security and confidentiality were ensured (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eData for this study were collected from four rural implementation sites\u0026mdash;Palwal, Sangrur, Pune, and Udaipur. Intrapartum care practices were assessed through direct, non-participant observation of 159 women admitted for delivery, while 143 government health facilities were evaluated for their readiness to provide routine and emergency maternal and newborn services. Observational data focused on critical labour room practices, whereas facility assessments examined the availability of human resources, infrastructure, essential equipment, and drugs. Findings revealed substantial variation across sites in adherence to recommended practices during admission, labour monitoring, delivery, and immediate newborn care.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIntrapartum Care Observations\u003c/h2\u003e \u003cp\u003eWe have presented the findings in four stages based on Intrapartum care and delivery processes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOn Admission:\u003c/h2\u003e \u003cp\u003eEffective intrapartum monitoring is central to preventing stillbirths, particularly through timely detection of maternal complications and fetal distress. However, our findings show wide variability across sites in the coverage and quality of monitoring practices.\u003c/p\u003e \u003cp\u003eBlood pressure on admission was recorded for the majority of women in Udaipur (86.1%) and Sangrur (81.8%), followed by Palwal (58.0%), but rarely in Pune (10.0%). Qualitative data from Pune and Palwal site reported incomplete adherence to referral protocols when pregnancy-induced hypertension was identified which suggesting the moderate coverage of BP checks, but also highlighting gaps in follow-up care. Poor documentation was observed at Pune site. Fetal heart sound (FHS) assessment was universal in Sangrur (100%), higher in Pune (96%) followed by Palwal (78.0%), but much lower in Udaipur (36.1%). The inconsistent application of this basic monitoring parameter suggests a missed opportunity to identify intrapartum complications.\u003c/p\u003e \u003cp\u003eFurther, cervical dilatation was assessed in over 70% of women in all sites with Pune (87.5%) being the highest. Monitoring of uterine contractions was common in Pune (75.0%) and Udaipur (86.1%) whereas not in Palwal. In case of Sangrur site the initial assessment of pregnant women arriving at the facility for delivery was found to be timely and covered all parameters with, at least a third of the women being identified as high-risk at the time of delivery. While this indicates the robustness of initial assessment, it also highlight\u0026rsquo;s the missed opportunity for management of HRPs during the antenatal care. The qualitative insights from Staff nurses of DH, SDH and CHCs with delivery facility, highlighted systemic challenges at this stage. They suggest that the gaps in implementation at this stage was primarily due to the multiple responsibilities handled by limited number of staff nurses (SNs) managing the both labour room and ANC duties with minimal support from the medical officers.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;We try to manage the emergency cases but if it\u0026rsquo;s not manageable then we refer the cases and sometimes we also refer the patient due unavailability of the staff\u0026thinsp;~\u0026thinsp;Palwal [Emergency pateint ko apne according manage karte hai, agar nahi hota refer karti hain, ya fir staff nhi to to pateint ko refer kar dete hain, CHC me 5 female staff nurses to chahiye hi par yha 4 hai\u0026rdquo;]\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLabor Monitoring:\u003c/h2\u003e \u003cp\u003eOur data on labour monitoring also showed inconsistent adherence to recommended practices. Per-vaginal (PV) examinations were conducted in 72.5% of women in Pune and 75.8% in Sangrur, but lower in Udaipur (50.0%). Artificial rupture of membranes (ARM) was frequent in Palwal (48%), but rare elsewhere (\u0026lt;\u0026thinsp;15%). Limited medical officer involvement and high workload among staff nurses contributed to unsupervised use of ARM and focus on third-stage oxytocin to prevent postpartum haemorrhage. Partograph initiation was limited across all sites, highest in Sangrur (24.2%). Partograph review prior to delivery was negligible across sites (\u0026lt;\u0026thinsp;35%), with zero use in Palwal and Pune, nonetheless qualitative data from Pune reported retrospective documentation of partograph. Overload and task shifting, with ANMs often assisting in labour without adequate supervision by medical officers was one of key reasons highlighted from the qualitative insights. This also led to missed routine checks like BP or FHR and it\u0026rsquo;s documentation. In Sangrur, real time partograph use was scarce and interaction with labour room staff reiterated manpower shortage and case load. Even though staff were available on call, frontline shortage and high workload reduced the quality of monitoring. Ongoing FHS monitoring was consistently high in Sangrur (100%) and Palwal (78%), but substantially lower in Udaipur (36.1%) and Pune (57.5%). Oxytocin use in the first stage of labour was rare across all sites (\u0026lt;\u0026thinsp;15%). Second-stage oxytocin use was high in Sangrur (75.8%), Pune reported it for 57.5%, while third-stage use was most common only in Palwal (66%). The in-depth interviews with ANMs suggests that cultural/familial pressure for \u0026ldquo;faster delivery/ outcome to reduce the suffering of the pregnant women\u0026rdquo; contributed to inappropriate oxytocin administration shortages of trained staff and fear of complications, which often may lead to a preference for caesarean delivery or early oxytocin use. In Udaipur, restrictive protocols prevented peripheral staff from administering oxytocin in early labour, explaining low uptake.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;We try to fill it (partograph) in real time but sometimes when there is patient load it becomes difficult as I am the only staff nurse in the department\u0026rdquo; ~Sangrur\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;They do not have the machine to check FHS. It has been in use recently; it was not there at the hospital earlier.\u0026rdquo; ~ Pune\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;We refer most cases which are primi or for LSCS. Madam was there earlier, we would still do primi cases but now we are doing 2nd gravida, third gravida which come dilated, 5\u0026ndash;6 fingers\u0026rdquo; ~ Sangrur\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDelivery Care \u0026amp; Newborn Care:\u003c/h2\u003e \u003cp\u003eIntrapartum oxytocin use (any stage) was highest in Palwal (84.0%) followed by Sangrur (75.8%), but was negligible in Pune (2.5%) and absent in Udaipur. Antibiotic use was highest in Sangrur (45.5%), but rare elsewhere (\u0026lt;\u0026thinsp;5%). Referrals from labour rooms were infrequent overall, except in Pune (22.5%). Staff nurses often lacked confidence in neonatal resuscitation and preferred immediate referral from lower-level facilities due to the absence of a paediatricians across all sites. In Udaipur, lower-level facilities restricted themselves to normal deliveries, with complicated cases routinely referred. Documentation of foetal distress was low across all sites (6.0% in Palwal; 12.1% in Sangrur and Udaipur). Resuscitation was most frequent in Sangrur (27.3%) compared to 8\u0026ndash;8.3% in rest of other sites. Across all deliveries, oxygen support was required by 22.2% of newborns in Udaipur and 12.1% in Sangrur, highlighting variability in immediate newborn care needs(Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;We give 5 units (1 ampule) by drip for inducing contractions after 5\u0026ndash;6 cm dilatation, which we also confirm using 3 fingers.\u0026rdquo; ~Sangrur\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;There is also a need for more child doctors at the municipal hospital since most people like us who face financial hardships are referred there. So, government must ensure the availability of doctors. They do not have enough services to offer to patients like me. A pediatrician should be available there. ~ Pune\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;High risk cases like CPD, hypertension, twins are usually referred to higher facility after giving first line of treatment as doctors are not available round the clock [High risk wale case ko ye normally refer hi karte hai jaise CPD, leaking aur koi hypertension hai, twins\u0026rsquo; pregnancy hai to first treatment dekar higher facility me refer karti hai, kyoki yaha par 24 hours ke liye doctors nahi hai].\u0026rdquo; ~Palwal\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssessment of Intrapartum care Indicators by Site\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePalwal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSangrur (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUdaipur\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePune\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e1. On Admission\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Blood pressure measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29(58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Foetal heart sound measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39(78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36(90%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Cervical Dilatation measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(72.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35(87.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Uterine Contraction measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30(75%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose partograph reviewed before delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e2. Labour Monitoring\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePV examinations done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29(72.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArtificial rupture of membranes performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartograph initiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Foetal heart sound measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39(78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23(57.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Cervical Dilatation measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(57.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(72.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25(62.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen whose Uterine Contraction measurement done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16(40%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen administered with oxytocin during 1st stage of labour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen administered with oxytocin during 2nd Stage of Labour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23(57.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen administered with oxytocin during 3rd Stage of labour (AMTSL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e3. Delivery care\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntrapartum use of oxytocin,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42(84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntrapartum antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e03(7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of Cases referred from the labour room\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(22.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e4. New born care\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFoetal distress documented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResuscitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFindings indicate notable site-level disparities, particularly in admission assessments, partograph use, and oxytocin administration practices. Sangrur showed higher coverage for several monitoring indicators, while Palwal had higher third stage oxytocin use. Udaipur demonstrated stronger uterine contraction monitoring but lagged in other intrapartum indicators. Pune underperformed in admission assessments but reported higher second stage oxytocin use and referral rate. These findings collectively suggest that even where basic monitoring is taking place, emergency protocols are either not being implemented or are inconsistently followed. The low adherence to life-saving interventions reflects systemic issues related to staff competency, workload, supervision, and availability of essential supplies. (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eInterpretation of Facility Assessment\u003c/h2\u003e \u003cp\u003eA total of 143 facilities were assessed across four sites (Palwal, Sangrur, Udaipur, and Pune) provision of quality intrapartum and newborn care. 88 facilities included district hospitals, sub-district hospitals, rural hospitals, and primary health centres and remaining facilities were sub-centres.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAvailability of Essential Newborn Care equipment by sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility readiness indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePalwal (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSangrur (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUdaipur\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePune\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNewborn resuscitation corner with functional radiant warmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(46.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (78.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuction apparatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal bag and masks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood transfusion or blood products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (11.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (52.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFunctional cardiotocography\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(57.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities having antenatal corticosteroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (73.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities having Methergine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (82.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities in which medical officer available 24*7 to attend to women in labour or the baby at birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (23.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (84.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities having triage area for pregnant women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (41.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (42.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities having ambulance available 24*7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(76.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (40.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities having oxygen central supply/concentrators/cylinders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (68.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of facilities having functional foetal doppler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (34.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEssential Newborn Care Equipment:\u003c/h2\u003e \u003cp\u003eMost facilities were equipped with a newborn resuscitation corner with a functional radiant warmer in Palwal (94.1%), Udaipur (46.9%), Pune (78.9%), and Sangrur (90.9%). Functional suction apparatus and appropriately sized neonatal bag and masks were available in more than 85% of facilities in Palwal, Udaipur, and Pune, but in 81.8% of Sangrur facilities\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCritical Maternal and Newborn Care Supplies:\u003c/h2\u003e \u003cp\u003eAvailability of oxytocin was high in Palwal (94.1%) and Udaipur (87.5%) but lower in Sangrur (50.0%). Antenatal corticosteroids were present in all facilities in Palwal (100%) followed by Udaipur (93.8%) and facilities in Sangrur with delivery points had 100% oxytocin use. Methergine availability was moderate across sites (Palwal 82.4%, Sangrur 55.0%, Udaipur 56.3%, Pune 68.4%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAdvanced Monitoring and Blood Products:\u003c/h2\u003e \u003cp\u003eBlood transfusion or blood product availability was limited in all sites except Pune (52.6%). Functional cardiotocography (CTG) was absent in Palwal, rare in Sangrur (9.1%), but higher in Udaipur (25.0%) and Pune (57.9%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eHuman Resources and Triage:\u003c/h2\u003e \u003cp\u003eTwenty-four-hour availability of a medical officer for labour and newborn care was highest in Pune (84.2%) and Udaipur (43.8%), but limited in Palwal (23.5%). Triage areas for pregnant women were most common in Sangrur (65.0%), but less frequent in Pune (42.1%) and Palwal (41.2%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eTransport and Oxygen Supply:\u003c/h2\u003e \u003cp\u003eAmbulance availability round-the-clock was highest in Pune (100%) and Sangrur (70.0%), and lower in Palwal (70.6%). Central oxygen supply, concentrators, or cylinders were available in most facilities in Palwal (94.1%), Udaipur (68.8%), and Pune (100%), but less so in Sangrur (75.0%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eFoetal Monitoring Devices:\u003c/h2\u003e \u003cp\u003eFunctional foetal dopplers were available in all Palwal facilities (100%), most Sangrur (80.0%) and Pune (100%), but in only 34.4% of Udaipur facilities.\u003c/p\u003e \u003cp\u003eFacility readiness varied widely between and within states. While basic newborn resuscitation equipment and essential drugs were generally available, gaps persisted in advanced monitoring capabilities, blood product availability, and consistent 24\u0026times;7 staffing, particularly in Palwal and Sangrur. Pune facilities demonstrated relatively better readiness in emergency transport, oxygen supply, and CTG availability. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAvailability of Critical Maternal and Newborn Drugs and Supplies by sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility readiness indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePalwal (n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSangrur (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUdaipur (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePune (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities having anticonvulsants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2(8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities having antihypertensive (injectable/ tablets)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(52.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22 (75.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnticonvulsants were available in less than half of facilities in all sites, with highest availability in Udaipur (46.0%) and Pune (44.8%), and lowest in Palwal (8.3%). Antihypertensives (injectable/tablets) were more widely available, ranging from 52.5% in Sangrur to 75.9% in Pune. (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAcross the four study sites, availability of key specialists and essential services varied considerably.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdvanced Monitoring, Blood Products, and Infrastructure Readiness by sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility readiness indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePalwal (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSangrur (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUdaipur (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePune (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities in which obstetrician available on call\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6(46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities in which paediatrician available on call\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4(30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(85.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities having Anaesthetists on call or Medical Officer trained in Anaesthesia available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2(15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(71.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities having Blood bank/ blood storage facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2(15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities having functional ultrasound 24*7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7(53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAvailability of key specialists and critical services varied considerably across study sites. Pune demonstrated the highest readiness, with all facilities (100%, 7/7) consistently having an obstetrician on call, followed by Sangrur (50%, 5/10), Udaipur (46.2%, 6/13), and Palwal (28.6%, 2/7). Paediatricians were most frequently available in Pune (85.7%, 6/7), with substantially lower proportions in Udaipur (30.8%, 4/13), Sangrur (20%, 2/10), and Palwal (14.3%, 1/7). The presence of an anaesthetist or trained medical officer for emergency obstetric care mirrored this trend, with Pune again leading (71.4%, 5/7) and much lower availability in Sangrur and Udaipur (each 20% and 15.4%, respectively) and Palwal (14.3%, 1/7). Access to blood bank or blood storage facilities was limited across all districts, found only in Udaipur (15.4%, 2/13), Sangrur (10%, 1/10), Pune (14.3%, 1/7), and Palwal (14.3%, 1/7). Regarding diagnostic capacity, functional 24\u0026times;7 ultrasound services were identified most frequently in Udaipur (53.8%, 7/13), followed by Sangrur (20%, 2/10), with no such service available in facilities surveyed in Palwal or Pune. (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This highlights persistent gaps in the availability of specialist staff and essential support services for comprehensive emergency obstetric and newborn care.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eQualitative findings for facility assessment\u003c/h2\u003e \u003cp\u003eAcross sites, facility assessment revealed a partial adequacy. While most facilities had basic infrastructure, essential drugs, and neonatal resuscitation equipment, advanced readiness indicators such as functional blood banks, cardiotocography, round-the-clock specialist coverage, and reliable referral systems were lacking. Palwal and Sangrur were particularly constrained by human resource shortages, with limited numbers of staff nurses and poor availability of specialists, leading to heavy multitasking and compromised emergency response. Udaipur demonstrated relatively good availability of essential drugs and oxygen support, yet had serious deficiencies in blood storage, CTG, and specialist coverage, compounded by weak infrastructure and geographic barriers. Pune performed better on most readiness indicators, with higher specialist availability, oxygen supply, and ambulance services, but still faced frontline staff shortages and dependency on referral systems for complications. Taken together, the findings indicate that although routine delivery care is feasible at most facilities, the capacity to provide comprehensive emergency obstetric and newborn care (CEmONC) is inadequate across all sites, limiting the ability to manage complications in a timely and effective manner.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;In the government facility, there was a waiting period of 1 to 1 and a half month for sonography.\u0026rdquo; (Pune)\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;No ambulance services were available. We had to arrange our vehicle for transport to the municipality hospital\u0026rdquo; (Pune)\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThis variation highlights critical service gaps, especially in paediatric coverage, anaesthesia services, and round-the-clock ultrasound availability. These gaps are particularly concerning given that all sites were implementing partners under the stillbirth reduction initiative. The findings suggest that existing programmatic efforts have yet to translate into consistent, high-quality service delivery, highlighting a disconnect between policy intent and ground-level implementation.\u003c/p\u003e\u003cp\u003eThe interpretation of observed practices and facility assessments clearly demonstrates that both routine monitoring and emergency readiness for intrapartum care are insufficient across all sites. While a few elements, such as FHS monitoring and cervical checks, show moderate coverage, core practices like partograph usage and emergency interventions are nearly absent. (Fig.\u0026nbsp;3). Facility limitations in skilled human resources, essential equipment, and emergency drugs mirror these clinical gaps and likely contribute to substandard outcomes. These findings indicate an urgent need for strategic intervention targeting health worker training, resource allocation, and supervision to improve adherence to evidence-based intrapartum care practices.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe quality of intrapartum treatment and facility preparedness varied significantly among India's rural districts, according to this multisite review. Complete intrapartum care guidelines were not always followed, even if several critical monitoring procedures, such as blood pressure checks and foetal heart sound (FHS) evaluations, were carried out regularly at a few clinics. Retrospective entries frequently replaced the place of real-time documentation, and partograph utilization remained remarkably low. Practices for administering oxytocin also differed; delays or improper use suggested a lack of oversight and inconsistent provider skill. These results were supported by qualitative insights, which showed that multitasking, excessive workload, and insufficient personnel were the primary barriers to successful intrapartum surveillance.\u003c/p\u003e \u003cp\u003eFacility readiness assessments discovered that most facilities had the basic medicines and baby care tools. But they were still significantly short of experts, blood transfusion services, and novel monitoring tools like cardiotocography (CTG). Pune demonstrated relatively better readiness and adherence compared to Palwal and Sangrur, where systemic challenges were more prominent. These findings underline the gap between national program expectations and ground-level implementation of evidence-based intrapartum practices.\u003c/p\u003e \u003cp\u003eOur findings are in accordance with past studies from India and other LMICs that demonstrated inadequate facility readiness and poor adherence to intrapartum care guidelines. Numerous studies conducted in various Indian states have documented low partograph use and insufficient foetal monitoring during labour, which directly contribute to preventable stillbirths and neonatal morbidity (\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Regular foetal heart monitoring and labour audits, for instance, were linked to a 59% decrease in intrapartum stillbirths over time, despite the fact that only 8.7% of labour cases used partographs, according to a multisite surveillance study from North India (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Similarly, a facility-based assessment in aspirational districts of Jharkhand, Odisha, and Uttarakhand revealed that foetal heart rate (FHR) monitoring was often done only once during labour, with minimal monitoring during the second stage, leading to missed opportunities for timely intervention (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). These trends are supported by comparable data from other LMICs. According to an Ethiopian study, the odds of stillbirth were 80% lower for women whose labour was tracked with a partograph than for those who did not (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Prolonged labour, substandard foetal monitoring, and infrequent ANC visits were found to be important factors in stillbirth in another Ethiopian study (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). All of these studies support the idea that, in settings with limited resources, one of the most prevalent causes of stillbirth is inadequate intrapartum monitoring, especially the failure to recognize and address foetal distress.\u003c/p\u003e \u003cp\u003eEvaluations of India's LaQshya and PMSMA programs also support our findings, demonstrating that states with more robust oversight, frequent audits, and provider mentoring have higher compliance rates with quality-of-care standards (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). However, as the SHRiSTI project highlighted, frontline staff frequently deal with a heavy caseload, conflicting programmatic demands, and a lack of supportive supervision, all of which make it difficult to consistently follow intrapartum protocols (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study confirms that quality deficiencies, not coverage gaps, are the cause of India's ongoing intrapartum stillbirth burden. Even though institutional deliveries are common, many facilities lack the procedures, knowledge, and accountability frameworks required to guarantee safe childbirth. Improving results requires enhancing real-time monitoring procedures, particularly making sure that partograph use becomes a regular, supervised activity. Promising outcomes concerning improving protocol adherence and early foetal distress detection have been demonstrated by digital labour monitoring tools and feedback-based audit mechanisms (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe lack of human resources at all levels highlights the necessity of skill-based capacity building, supportive supervision, and task-sharing techniques. When integrated into mentorship programs, regular simulation-based training for obstetric emergencies may boost provider confidence and minimize clinical errors. For timely management of complications, it is crucial to guarantee 24-hour access to Comprehensive Emergency Obstetric and Newborn Care (CEmONC) services, including blood transfusion and specialist availability.\u003c/p\u003e \u003cp\u003eMore uniformity in implementation can be achieved at the policy level by coordinating current national programs with WHO's Quality of Care for Maternal and Newborn Health Standards. Accountability and evidence-based action would be encouraged by establishing regular quality audits, reviewing maternal and perinatal deaths, and connecting facility data to perinatal outcomes.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study's mixed-methods approach, which combined qualitative insights, facility assessment, and direct observation, is one of its main strengths. This all-encompassing viewpoint made it possible to triangulate the evidence and find systemic and operational factors that contribute to subpar intrapartum quality. The findings are more broadly applicable due to the multisite coverage in four different settings.\u003c/p\u003e \u003cp\u003eHowever, the possibility of observer bias (Hawthorne effect) cannot be excluded, as staff behaviour might have changed during observation. Assessments of the facilities were a cross-sectional snapshot and might not have taken into account changes in staffing or supply availability over time. The exclusion of private sector facilities restricts extrapolation to all settings for childbirth. The study does, however, provide important evidence regarding the ongoing intrapartum quality disparities that contribute to poor perinatal outcomes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRecommendations and Future Directions\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStrengthen intrapartum monitoring with digital tools, supportive supervision, as well as mandatory partograph audits.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIncrease the availability of human resources through rotation planning, task sharing, and ongoing skill-based training.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMaintaining vital supplies, blood storage, and referral connections will help to ensure that the facility is prepared for emergency response.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEstablish regular labour room audits and stillbirth review committees to codify cycles of quality improvement.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFacilitate ongoing learning and accountability, integrate data systems that connect perinatal outcomes with intrapartum practices.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eFuture studies should assess how effectively structured quality improvement models, like mentorship-based LaQshya reinforcement and digital partographs, reduce intrapartum stillbirths and enhance maternal outcomes in all settings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDespite India\u0026rsquo;s progress in institutional delivery, quality of intrapartum care continues to determine perinatal outcomes. Strengthening labour monitoring, building workforce capacity, and ensuring facility preparedness are essential to achieve Every Newborn Action Plan goal of \u0026le;\u0026thinsp;10 stillbirths per 1,000 births by 2035.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical approval for this study was obtained from KEM Hospital Research Centre Institutional Ethics Committee (Reference No.\u0026nbsp;KEMHRC/RVM/EC/1964) for Pune site; Institutional Review Board, International Institute of Health Management Research Delhi (Ref no: IRB/2024-2025/01) for Sangrur site; ICMR-NIRNCD institutional ethics committee (Ref no: IEC-NIIRNCD/2023/DEC/FR/004) for Jodhpur site; \u0026nbsp;and Society of Applied statistics Institutional Ethics committee (Ref No: SAS/ERC/ICMR Stillbirths Study/2024) . Administrative permissions were obtained at district and facility levels prior to data collection. The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants before data collection, including consent for audio recording of interviews. Confidentiality and data security were maintained throughout the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be made available on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All authors declare that they have no completing interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This work was supported by the Indian Council of Medical Research (ICMR) [grant ID: 5/7/BMIPR/2022-RCN].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRP, KK, GD, NA, BGP, SM, SK, SBN, RB, AKP, DG, VK, SM and RM jointly developed the study concept and design. RP, KK, NM, GD, NA, BGP, SM, SR and SB coordinated and supervised data collection across the participating sites. Data analysis and interpretation were carried out by RP, KK, NM, GD, AKP, RB and NA. The initial draft of the manuscript was prepared by RP, KK, NM, GD, AKP, DG, SK and RM. All authors\u0026mdash;including MG, SD, IK, SY and other collaborators\u0026mdash;contributed to reviewing and refining the manuscript and provided important intellectual input. Every author approved the final version of the manuscript and accepts responsibility for the accuracy and integrity of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the contributions of Dr. Pranay Vats, Dr. Sonia Maurya, and Mr. Aditya Bhatt from research team (SAS) towards data generation and analysis, part of which has been incorporated in this manuscript. Additionally, Palwal research team is grateful to Mission Director National Health Mission Haryana, Director, Maternal and Child Health, NHM, Haryana and Chief Medical officer of Palwal district for their consistent support during implementation study at Haryana-site. We are grateful to the Indian Council of Medical Research (ICMR) for their support and the team from the State Health Systems Resource Centre (SHSRC), Pune for their technical assistance throughout the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDa Silva FT, Gonik B, McMillan M, Keech C, Dellicour S, Bhange S, et al. Stillbirth: Case definition and guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine. 2016;34(49):6057\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerinatal surveillance and prevention of birth defects. : Progress Review [Internet]. 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Qual Quant [Internet]. 2009 Mar 1 [cited 2025 Aug 4];43(2):265\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11135-007-9105-3\u003c/span\u003e\u003cspan address=\"10.1007/s11135-007-9105-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe quality of. mixed methods studies in health services research | EQUATOR Network [Internet]. 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BMC Pregnancy Childbirth. 2021;21:377.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaturvedi S, Randive B, Diwan V, De Costa A. Quality of obstetric referral services in India: A situational analysis. PLoS ONE. 2015;10(9):e0138499.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaye A, Woldemichael K, Getachew Y. Use of partograph and its effect on birth outcomes at Felege Hiwot Comprehensive Specialized Hospital, Ethiopia. BMC Res Notes. 2019;12(1):603.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesta M, Hiko D, Misganu G. Determinants of stillbirths among women who gave birth at Hawassa University Comprehensive Specialized Hospital, Ethiopia. Maternal Health Neonatol Perinatol. 2021;7(1):9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Health and Family Welfare. Government of India. LaQshya \u0026ndash; Labour Room Quality Improvement Initiative. National Guidelines. New Delhi: MoHFW; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Health and Family Welfare. Pradhan Mantri Surakshit Matritva Abhiyan (PMSMA): Operational Guidelines. New Delhi: MoHFW; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGopalakrishnan S, Sharma M, Ramesh B. Understanding workload and performance challenges among labour room staff in public facilities in India. Indian J Community Med. 2020;45(2):165\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrivastava A, Sharma N, Murthy GVS. Barriers to adherence with intrapartum care protocols among nurses in India: a qualitative study. BMC Health Serv Res. 2018;18:472.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoucheraud C, Worku A, Tesfaye M, et al. Improving quality of intrapartum care in low-resource settings through continuous monitoring and feedback. Reprod Health. 2019;16:163.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Emergency obstetric care, Facility readiness, Health system, Intrapartum care, Maternal health, Mixed-methods, Rural India, Stillbirth prevention","lastPublishedDoi":"10.21203/rs.3.rs-8336003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8336003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn India, stillbirth is still a significant, avoidable pregnancy outcome that reflects ongoing deficiencies in the standard of care for expectant mothers and newborns. Even though institutional deliveries have improved, a significant percentage of stillbirths happen during the intrapartum phase, frequently as a result of poor monitoring, a failure to recognize complications promptly, and a lack of facility readiness.\u003c/p\u003e\n\u003cp\u003eThis study aimed to assess the quality of intrapartum care and facility readiness across four diverse rural districts in India, identify key systemic and contextual challenges, and inform improvement strategies for reducing stillbirths.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the formative phase of an implementation research project, we carried out a sequential mixed-methods study. Direct, non-participating observations of 159 labouring women and readiness evaluations of 134 public health facilities comprised the quantitative component. Focus groups and in-depth interviews with healthcare professionals and community stakeholders were used to gather qualitative data. Descriptive statistics and thematic analysis were used to triangulate the data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdherence to evidence-based intrapartum care practices varied significantly between sites. Assessments of fetal heart sound and blood pressure were among the indicators that were not consistently monitored. Real-time documentation was frequently lacking, and partograph use was generally low. Procedures for administering oxytocin and handling emergencies varied. Assessments of facility preparedness showed that while basic newborn supplies and necessary medications were typically available, there was a lack of access to specialists, blood transfusion services, and sophisticated monitoring equipment (such as CTG). According to qualitative findings, multitasking, excessive workloads, and staff shortages are the main obstacles in providing quality care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite high rates of institutional births, rural India's lack of adequate intrapartum care and facility preparedness impedes efforts to lower the number of stillbirths. There is an urgent need for targeted interventions to improve real-time labor monitoring, increase workforce capacity, and deliver comprehensive emergency obstetric care. To meet national stillbirth reduction targets, strategies for implementing data-driven audits and embedding quality improvement cycles are essential.\u003c/p\u003e\n\u003cp\u003eKeywords: Emergency obstetric care, Facility readiness, Health system, Intrapartum care, Maternal health, Mixed-methods, Rural India, Stillbirth prevention.\u003c/p\u003e","manuscriptTitle":"Can we prevent stillbirths in India: A mixed-methods multisite study assessing Intrapartum care and public health facilities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 12:42:37","doi":"10.21203/rs.3.rs-8336003/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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