More than two-thirds of newborn lives could be saved worldwide if evidence-based interventions were successfully implemented. We developed the NeoTree application to improve quality of newborn care in resource-poor countries. The NeoTree is a fully integrated digital health intervention that combines immediate data capture, entered by healthcare workers (HCW) on admission, while simultaneously providing them with evidence-based clinical decision support and newborn care education. We conducted a mixed-methods intervention development study, codeveloping and testing the NeoTree prototype with HCWs in a district hospital in Malawi. Focus groups explored the acceptability and feasibility of digital health solutions before and after implementation of the NeoTree in the clinical setting. One-to-one theoretical usability workshops and a 1-month clinical usability study informed iterative changes, gathered process and clinical data, System Usability Scale (SUS) and perceived improvements in quality of care. HCWs perceived the NeoTree to be acceptable and feasible. Mean SUS before and after the clinical usability study were high at 80.4 and 86.1, respectively (above average is >68). HCWs reported high-perceived improvements in quality of newborn care after using the NeoTree on the ward. They described improved confidence in clinical decision-making, clinical skills, critical thinking and standardisation of care. Identified factors for successful implementation included a technical support worker. Coproduction, mixed-methods approaches and user-focused iterative development were key to the development of the NeoTree prototype, which was shown to be an agile, acceptable, feasible and highly usable tool with the potential to improve the quality of newborn care in resource-poor settings.

Autism is a global phenomenon. Yet, there is a dearth of knowledge of how it is understood and its impact in low-income countries. We examined parents’ and professionals’ understanding of autism in one low-income country, Nepal. We conducted focus groups and semi-structured interviews with parents of autistic and non-autistic children and education and health professionals from urban and rural settings (n = 106), asking questions about typical and atypical development and presenting vignettes of children to prompt discussion. Overall, parents of typically developing children and professionals had little explicit awareness of autism. They did, however, use some distinctive terms to describe children with autism from children with other developmental conditions. Furthermore, most participants felt that environmental factors, including in-utero stressors and birth complications, parenting style and home or school environment were key causes of atypical child development and further called for greater efforts to raise awareness and build community capacity to address autism. This is the first study to show the striking lack of awareness of autism by parents and professionals alike. These results have important implications for future work in Nepal aiming both to estimate the prevalence of autism and to enhance support available for autistic children and their families.

Background: Despite increasing rates of facility-based deliveries, neonatal mortality rates remain persistently high in low-resource settings (LRS). This has catalysed international focus on understanding and enabling quality newborn care. We aimed to understand persistent barriers to Quality of Care (QoC) and to identify quality improvement priorities from the perspective of a panel of neonatal experts with first-hand experience of delivering newborn care in low-resource settings (LRS). Methods: We conducted 13 semi-structured interviews with neonatal health experts via Skype. All interviews were recorded and transcribed verbatim. We adopted an inductive thematic analytical approach. Ethical approvals were not required. Results: Twenty-two experts were invited to participate, of whom 16 responded and 13 agreed to take part (five neonatologists, six paediatricians and two advanced neonatal nurse practitioners). Participants had a mean of 13 (±7 SD) years working in LRS. Lack of physical resources including basic equipment and infrastructure such as running water, combined with limited human resources, education and specialist neonatal training were cited as key barriers to delivering quality care. In addition, weak leadership at the community, local and national level were thought to hinder progress. Poor communication within clinical teams, limited documentation and lack of standardised and locally appropriate guidelines were also identified as challenges. Digital technologies were perceived to have potential for data capture and enabling standardised care. However, some highlighted that unreliable internet access and possible stigma may hinder implementation. Conclusions: With less than 10 years to reach the Sustainable Development Goals (SDGs), it is critical to ensure access to quality care for all sick and vulnerable newborns admitted to health facilities. Clinical leaders in low resource settings need to be empowered to define local agendas and advocate for critical resources in order to close the gap between local and global quality of care priorities.

Few data exist on the prevalence of autism in low-income countries. We translated, adapted and tested the acceptability of a Nepali-language version of a screening tool for autism (Autism Quotient-10). Using this tool, we estimated autism prevalence in 4098 rural Nepali children aged 9–13 years. Fourteen children scored > 6 out of 10, indicative of elevated autistic symptomatology, of which 13 also screened positive for disability. If the AQ-10 screening tool is as sensitive and specific in the Nepali population as it is in the UK, this would yield an estimated true prevalence of 3 in 1000 (95% confidence interval 2–5 in 1000). Future research is required to validate this tool through in-depth assessments of high-scoring children.

Introduction: Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy, facilitating earlier treatment for cases and avoiding antibiotic overuse. Neonates in low-income and middle-income countries (LMICs) are disproportionately affected by sepsis, yet no review has comprehensively synthesised evidence for CPMs validated in this setting. Methods: We performed a scoping review of CPMs to diagnose neonatal sepsis using Ovid MEDLINE, Ovid Embase, Scopus, Web of Science, Global Index Medicus and the Cochrane Library. The most recent searches were performed on 16 June 2024. We included studies published in English or Spanish that validated a new or existing CPM for neonatal sepsis in any healthcare setting in an LMIC. Studies were excluded if they validated a prognostic model or where data for neonates could not be separated from a larger paediatric population. Studies were selected by two independent reviewers and summarised by narrative synthesis. Results: From 4598 unique records, we included 82 studies validating 44 distinct models in 24 252 neonates. Most studies were set in neonatal intensive or special care units (n=64, 78%) in middle-income countries (n=81, 99%) and included neonates already suspected of sepsis (n=58, 71%). Only four studies (5%) were set in the WHO African region, and only one study included data from a low-income country. Two-thirds of CPMs (n=30) required laboratory parameters, and three-quarters (n=34) were only validated in one study. Conclusion: Our review highlights several literature gaps, particularly a paucity of studies validating models in the lowest-income countries where neonatal sepsis is most prevalent, and models for the undifferentiated neonatal population that do not rely on laboratory tests. Furthermore, heterogeneity in study populations, definitions of sepsis and reporting of models inhibits meaningful comparison between studies and may hinder progress towards useful diagnostic tools.

Variation in paediatric inpatient length of stay exists – whether this is driven by differences in patient characteristics or health service delivery is unclear. We will test the hypotheses that higher levels of deprivation are associated with prolonged length of stay and that differences in prolonged length of stay across 2 hospitals will be explained by demographic, clinical and process factors. This is a retrospective cohort study of 2889 children aged less than 16 years admitted from 1st April 2009 to 30th March 2010. Administrative data were used from two UK hospitals whose Accident and Emergency (A&E) departments were paediatric and adult physician led respectively. The main outcome was prolonged length of stay defined as greater than or equal to the mean (1.8 days). Sensitivity analyses defined prolonged length of stay as greater than the median (1 day). Demographic, clinical and process characteristics were examined. Socio-economic position was measured by Income Deprivation Affecting Children Index. Multivariable logistic and linear regression analyses were performed. We did not find a consistent association between length of stay and socio-economic position, using a variety of definitions of length of stay. In contrast, adjusted for age, gender, socio-economic position, ethnicity, final diagnosis, number of hospital admissions, source of admission, and timing of admission, admission to the adult led A&E hospital was more strongly associated with prolonged length of stay (Odds Ratio 1.41, 95% Confidence Interval 1.16, 1.71). Local variation in paediatric inpatient length of stay was not explained by demographic, clinical or process factors, but could have been due to residual confounding by medical complexity. Length of stay was not consistently associated with socio-economic position suggesting that length of stay is a function of health service not the determinants of health. Analyses of these types of data would be strengthened by measures of complexity and adverse events.