Introduction Kangaroo Mother Care (KMC) is the practice of early, continuous and prolonged skin-to-skin contact between the mother and the baby with exclusive breastfeeding. Despite clear evidence of impact in improving survival and health outcomes among low birth weight infants, KMC coverage has remained low and implementation has been limited. Consequently, only a small fraction of newborns that could benefit from KMC receive it. Methods and analysis This implementation research project aims to develop and evaluate district-level models for scaling up KMC in India and Ethiopia that can achieve high population coverage. The project includes formative research to identify barriers and contextual factors that affect implementation and utilisation of KMC and design scalable models to deliver KMC across the facility-community continuum. This will be followed by implementation and evaluation of these models in routine care settings, in an iterative fashion, with the aim of reaching a successful model for wider district, state and national-level scale-up. Implementation actions would happen at three levels: ‘pre-KMC facility’—to maximise the number of newborns getting to a facility that provides KMC; ‘KMC facility’—for initiation and maintenance of KMC; and ‘post-KMC facility’—for continuation of KMC at home. Stable infants with birth weight<2000 g and born in the catchment population of the study KMC facilities would form the eligible population. The primary outcome will be coverage of KMC in the preceding 24 hours and will be measured at discharge from the KMC facility and 7 days after hospital discharge. Ethics and dissemination Ethics approval was obtained in all the project sites, and centrally by the Research Ethics Review Committee at the WHO. Results of the project will be submitted to a peer-reviewed journal for publication, in addition to national and global level dissemination. Study status WHO approved protocol: V.4—12 May 2016—Protocol ID: ERC 2716. Study implementation beginning: April 2017. Study end: expected March 2019. Trial registration number Community Empowerment Laboratory, Uttar Pradesh, India (ISRCTN12286667); St John's National Academy of Health Sciences, Bangalore, India and Karnataka Health Promotion Trust, Bangalore, India (CTRI/2017/07/008988); Society for Applied Studies, Delhi (NCT03098069); Oromia, Ethiopia (NCT03419416); Amhara, SNNPR and Tigray, Ethiopia (NCT03506698).

As the proportion of facility‐based births increases, so does the need to ensure that mothers and their newborns receive quality care. Developing facility‐oriented obstetric and neonatal training programs grounded in principles of teamwork utilizing simulation‐based training for emergency response is an important strategy for improving the quality care. This study uses 3 dimensions of the Kirkpatrick Model to measure the impact of PRONTO International (PRONTO) simulation‐based training as part of the Linda Afya ya Mama na Mtoto (LAMMP, Protect the Health of mother and child) in Kenya. Changes in knowledge of obstetric and neonatal emergency response, self‐efficacy, and teamwork were analyzed using longitudinal, fixed‐effects, linear regression models. Participants from 26 facilities participated in the training between 2013 and 2014. The results demonstrate improvements in knowledge, self‐efficacy, and teamwork self‐assessment. When comparing pre‐Module I scores with post‐training scores, improvements range from 9 to 24 percentage points (p values < .0001 to .026). Compared to baseline, post‐Module I and post‐Module II (3 months later) scores in these domains were similar. The intervention not only improved participant teamwork skills, obstetric and neonatal knowledge, and self‐efficacy but also fostered sustained changes at 3 months. The proportion of facilities achieving self‐defined strategic goals was high: 95.8% of the 192 strategic goals. Participants rated the PRONTO intervention as extremely useful, with an overall score of 1.4 out of 5 (1, extremely useful; 5, not at all useful). Evaluation of how these improvements affect maternal and perinatal clinical outcomes is forthcoming.

Globally, there were 2.7 million neonatal deaths in 2015. Significant mortality reduction could be achieved by improving care in low- and middle-income countries (LMIC), where the majority of deaths occur. Determining the physical readiness of facilities to identify and manage complications is an essential component of strategies to reduce neonatal mortality. We developed clinical cascades for 6 common neonatal conditions then utilized these to assess 23 health facilities in Kenya and Uganda at 2 time-points in 2016 and 2017. We calculated changes in resource availability over time by facility using McNemar’s test. We estimated mean readiness and loss of readiness for the 6 conditions and 3 stages of care (identification, treatment, monitoring-modifying treatment). We estimated overall mean readiness and readiness loss across all conditions and stages. Finally, we compared readiness of facilities with a newborn special care unit (NSCU) to those without using the two-sample test of proportions. The cascade model estimated mean readiness of 26.3–26.6% across the 3 stages for all conditions. Mean readiness ranged from 11.6% (respiratory distress-apnea) to 47.8% (essential newborn care) across both time-points. The model estimated overall mean readiness loss of 30.4–31.9%. There was mild to moderate variability in the timing of readiness loss, with the majority occurring in the identification stage. Overall mean readiness was higher among facilities with a NSCU (36.8%) compared to those without (20.0%). The cascade model provides a novel approach to quantitatively assess physical readiness for neonatal care. Among 23 facilities in Kenya and Uganda, we identified a consistent pattern of 30–32% readiness loss across cascades and stages. This aggregate measure could be used to monitor and compare readiness at the facility-, health system-, or national-level. Estimates of readiness and loss of readiness may help guide strategies to improve care, prioritize resources, and promote neonatal survival in LMICs.

Background: In Ethiopia, neonatal mortality accounts for approximately 54% of under-five deaths with the majority of these deaths driven by infections. Possible Severe Bacterial Infection (PSBI) in neonates is a syndromic diagnosis that non-clinical health care providers use to identify and treat newborns with signs of sepsis. In low- and middle–income countries, referral to a hospital may not be feasible due to transportation, distance or finances. Growing evidence suggests health extension workers (HEWs) can identify and manage PSBI at the community level when referral to a hospital is not possible. However, community-based PSBI care strategies have not been widely scaled-up. This study aims to understand general determinants of household-level care as well as household care seeking and decision-making strategies for neonatal PSBI symptoms. Methods: We conducted eleven focus group discussions (FGDs) to explore illness recognition and care seeking intentions from four rural kebeles in Amhara, Ethiopia. FGDs were conducted among mothers, fathers and households with recruitment stratified among households that have had a newborn with at least one symptom of PSBI (Symptomatic Group), and households that have had a newborn regardless of the child’s health status (Community Group). Data were thematically analyzed using MAXQDA software. Results: Mothers were described as primary caretakers of the newborn and were often appreciated for making decisions for treatment, even when the father was not present. Type of care accessed was often dependent on conceptualization of the illness as simple or complex. When symptoms were not relieved with clinical care, or treatments at facilities were perceived as ineffective, alternative methods were sought. Most participants identified the health center as a reliable facility. While designed to be the first point of access for primary care, health posts were not mentioned as locations where families seek clinical treatment. Conclusions: This study describes socio-contextual drivers for PSBI treatment at the community level. Future programming should consider the role community members have in planning interventions to increase demand for neonatal care at primary facilities. Encouragement of health post utilization could further allow for heightened accessibility-acceptability of a simplified PSBI regimen.

Globally, the rate of reduction in delivery-associated maternal and perinatal mortality has been slow compared to improvements in post-delivery mortality in children under five. Improving clinical readiness for basic obstetric emergencies is crucial for reducing facility-based maternal deaths. Emergency readiness is commonly assessed using tracers derived from the maternal signal functions model. We compare emergency readiness using the signal functions model and a novel clinical cascade. The cascades model readiness as the proportion of facilities with resources to identify the emergency (stage 1), treat it (stage 2) and monitor-modify therapy (stage 3). Data were collected from 44 Kenyan clinics as part of an implementation trial. Although most facilities (77.0%) stock maternal signal function tracer drugs, far fewer have resources to practically identify and treat emergencies. In hypertensive emergencies for example, 38.6% of facilities have resources to identify the emergency (Stage 1 readiness, including sphygmomanometer, stethoscope, urine collection device, protein test). 6.8% have the resources to treat the emergency (Stage 2, consumables (IV Kit, fluids), durable goods (IV pole) and drugs (magnesium sulfate and hydralazine). No facilities could monitor or modify therapy (Stage 3). Across five maternal emergencies, the signal functions overestimate readiness by 54.5%. A consistent, step-wise pattern of readiness loss across signal functions and care stage emerged and was profoundly consistent at 33.0%. Comparing estimates from the maternal signal functions and cascades illustrates four themes. First, signal functions overestimate practical readiness by 55%. Second, the cascade’s intuitive indicators can support cross-sector health system or program planners to more precisely measure and improve emergency care. Third, adding few variables to existing readiness inventories permits step-wise modeling of readiness loss and can inform more precise interventions. Fourth, the novel aggregate readiness loss indicator provides an innovative and intuitive approach for modeling health system emergency readiness. Additional testing in diverse contexts is warranted.