Search

Background: The emergence of COVID-19 precipitated containment policies (e.g., lockdowns, school closures, etc.). These policies disrupted healthcare, potentially eroding gains for Sustainable Development Goals including for neonatal mortality. Our analysis aimed to evaluate indirect effects of COVID-19 containment policies on neonatal admissions and mortality in 67 neonatal units across Kenya, Malawi, Nigeria, and Tanzania between January 2019 and December 2021., Methods: The Oxford Stringency Index was applied to quantify COVID-19 policy stringency over time for Kenya, Malawi, Nigeria, and Tanzania. Stringency increased markedly between March and April 2020 for these four countries (although less so in Tanzania), therefore defining the point of interruption. We used March as the primary interruption month, with April for sensitivity analysis. Additional sensitivity analysis excluded data for March and April 2020, modelled the index as a continuous exposure, and examined models for each country. To evaluate changes in neonatal admissions and mortality based on this interruption period, a mixed effects segmented regression was applied. The unit of analysis was the neonatal unit (n = 67), with a total of 266,741 neonatal admissions (January 2019 to December 2021)., Results: Admission to neonatal units decreased by 15% overall from February to March 2020, with half of the 67 neonatal units showing a decline in admissions. Of the 34 neonatal units with a decline in admissions, 19 (28%) had a significant decrease of ≥ 20%. The month-to-month decrease in admissions was approximately 2% on average from March 2020 to December 2021. Despite the decline in admissions, we found no significant changes in overall inpatient neonatal mortality. The three sensitivity analyses provided consistent findings., Conclusion: COVID-19 containment measures had an impact on neonatal admissions, but no significant change in overall inpatient neonatal mortality was detected. Additional qualitative research in these facilities has explored possible reasons. Strengthening healthcare systems to endure unexpected events, such as pandemics, is critical in continuing progress towards achieving Sustainable Development Goals, including reducing neonatal deaths to less than 12 per 1000 live births by 2030., (© 2024. The Author(s).)

Preterm birth (< 37 weeks gestation) complications are the leading cause of neonatal mortality. Early-warning scores (EWS) are charts where vital signs (e.g., temperature, heart rate, respiratory rate) are recorded, triggering action. To evaluate whether a neonatal EWS improves clinical outcomes in low-middle income countries, a randomised trial is needed. Determining whether the use of a neonatal EWS is feasible and acceptable in newborn units, is a prerequisite to conducting a trial. We implemented a neonatal EWS in three newborn units in Kenya. Staff were asked to record infants' vital signs on the EWS during the study, triggering additional interventions as per existing local guidelines. No other aspects of care were altered. Feasibility criteria were pre-specified. We also interviewed health professionals (n = 28) and parents/family members (n = 42) to hear their opinions of the EWS. Data were collected on 465 preterm and/or low birthweight (< 2.5 kg) infants. In addition to qualitative study participants, 45 health professionals in participating hospitals also completed an online survey to share their views on the EWS. 94% of infants had the EWS completed at least once during their newborn unit admission. EWS completion was highest on the day of admission (93%). Completion rates were similar across shifts. 15% of vital signs triggered escalation to a more senior member of staff. Health professionals reported liking the EWS, though recognised the biggest barrier to implementation was poor staffing. Newborn unit infant to staff ratios varied between 10 and 53 staff per 1 infant, depending upon time of shift and staff type. A randomised trial of neonatal EWS in Kenya is possible and acceptable, though adaptations are required to the form before implementation., (© 2024. The Author(s).)

Background: Reports on hypothermia from high-burden countries like Kenya amongst sick newborns often include few centers or relatively small sample sizes., Objectives: This study endeavored to describe: (i) the burden of hypothermia on admission across 21 newborn units in Kenya, (ii) any trend in prevalence of hypothermia over time, (iii) factors associated with hypothermia at admission, and (iv) hypothermia's association with inpatient neonatal mortality., Methods: A retrospective cohort study was conducted from January 2020 to March 2023, focusing on small and sick newborns admitted in 21 NBUs. The primary and secondary outcome measures were the prevalence of hypothermia at admission and mortality during the index admission, respectively. An ordinal logistic regression model was used to estimate the relationship between selected factors and the outcomes cold stress (36.0°C-36.4°C) and hypothermia (<36.0°C). Factors associated with neonatal mortality, including hypothermia defined as body temperature below 36.0°C, were also explored using logistic regression., Results: A total of 58,804 newborns from newborn units in 21 study hospitals were included in the analysis. Out of these, 47,999 (82%) had their admission temperature recorded and 8,391 (17.5%) had hypothermia. Hypothermia prevalence decreased over the study period while admission temperature documentation increased. Significant associations were found between low birthweight and very low (0-3) APGAR scores with hypothermia at admission. Odds of hypothermia reduced as ambient temperature and month of participation in the Clinical Information Network (a collaborative learning health platform for healthcare improvement) increased. Hypothermia at admission was associated with 35% (OR 1.35, 95% CI 1.22, 1.50) increase in odds of neonatal inpatient death., Conclusions: A substantial proportion of newborns are admitted with hypothermia, indicating a breakdown in warm chain protocols after birth and intra-hospital transport that increases odds of mortality. Urgent implementation of rigorous warm chain protocols, particularly for low-birth-weight babies, is crucial to protect these vulnerable newborns from the detrimental effects of hypothermia., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer LD declared shared affiliation with one of the authors MO to the handling editor at the time of the review., (© 2024 Wainaina, Ogero, Mumelo, Wairoto, Mbevi, Tuti, Mwaniki, Irimu, English, Aluvaala and The Clinical Information Network Author Group.)

Background: Thirty million small and sick newborns worldwide require inpatient care each year. Many receive antibiotics for clinically diagnosed infections without blood cultures, the current 'gold standard' for neonatal infection detection. Low neonatal blood culture use hampers appropriate antibiotic use, fuelling antimicrobial resistance (AMR) which threatens newborn survival. This study analysed the gap between blood culture use and antibiotic prescribing in hospitals implementing with Newborn Essential Solutions and Technologies (NEST360) in Kenya, Malawi, Nigeria, and Tanzania., Methods: Inpatient data from every newborn admission record (July 2019-August 2022) were included to describe hospital-level blood culture use and antibiotic prescription. Health Facility Assessment data informed performance categorisation of hospitals into four tiers: (Tier 1) no laboratory, (Tier 2) laboratory but no microbiology, (Tier 3) neonatal blood culture use < 50% of newborns receiving antibiotics, and (Tier 4) neonatal blood culture use > 50%., Results: A total of 144,146 newborn records from 61 hospitals were analysed. Mean hospital antibiotic prescription was 70% (range = 25-100%), with 6% mean blood culture use (range = 0-56%). Of the 10,575 blood cultures performed, only 24% (95%CI 23-25) had results, with 10% (10-11) positivity. Overall, 40% (24/61) of hospitals performed no blood cultures for newborns. No hospitals were categorised as Tier 1 because all had laboratories. Of Tier 2 hospitals, 87% (20/23) were District hospitals. Most hospitals could do blood cultures (38/61), yet the majority were categorised as Tier 3 (36/61). Only two hospitals performed > 50% blood cultures for newborns on antibiotics (Tier 4)., Conclusions: The two Tier 4 hospitals, with higher use of blood cultures for newborns, underline potential for higher blood culture coverage in other similar hospitals. Understanding why these hospitals are positive outliers requires more research into local barriers and enablers to performing blood cultures. Tier 3 facilities are missing opportunities for infection detection, and quality improvement strategies in neonatal units could increase coverage rapidly. Tier 2 facilities could close coverage gaps, but further laboratory strengthening is required. Closing this culture gap is doable and a priority for advancing locally-driven antibiotic stewardship programmes, preventing AMR, and reducing infection-related newborn deaths., (© 2023. The Author(s).)

Poor-quality paediatric and neonatal care in district hospitals in low-income and middle-income countries (LMICs) was first highlighted more than 20 years ago. WHO recently developed more than 1000 paediatric and neonatal quality indicators for hospitals. Prioritising these indicators should account for the challenges in producing reliable process and outcome data in these settings, and their measurement should not unduly narrow the focus of global and national actors to reports of measured indicators. A three-tier, long-term strategy for the improvement of paedicatric and neonatal care in LMIC district hospitals is needed, comprising quality measurement, governance, and front-line support. Measurement should be better supported by integrating data from routine information systems to reduce the future cost of surveys. Governance and quality management processes need to address system-wide issues and develop supportive institutional norms and organisational culture. This strategy requires governments, regulators, professions, training institutions, and others to engage beyond the initial consultation on indicator selection, and to tackle the pervasive constraints that undermine the quality of district hospital care. Institutional development must be combined with direct support to hospitals. Too often the focus of indicator measurement as an improvement strategy is on reporting up to regional or national managers, but not on providing support down to hospitals to attain quality care., Competing Interests: Declaration of interests The authors all receive funding for research linked to the improvement of hospital care in low-income and middle-income countries. ME, TD, JA, and GI have or have had roles as technical advisers to WHO in the fields of newborn and child health. MM declares no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: In an external validation study, model recalibration is suggested once there is evidence of poor model calibration but with acceptable discriminatory abilities. We identified four models, namely RISC-Malawi (Respiratory Index of Severity in Children) developed in Malawi, and three other predictive models developed in Uganda by Lowlaavar et al. (2016). These prognostic models exhibited poor calibration performance in the recent external validation study, hence the need for recalibration., Objective: In this study, we aim to recalibrate these models using regression coefficients updating strategy and determine how much their performances improve., Methods: We used data collected by the Clinical Information Network from paediatric wards of 20 public county referral hospitals. Missing data were multiply imputed using chained equations. Model updating entailed adjustment of the model's calibration performance while the discriminatory ability remained unaltered. We used two strategies to adjust the model: intercept-only and the logistic recalibration method., Results: Eligibility criteria for the RISC-Malawi model were met in 50,669 patients, split into two sets: a model-recalibrating set (n = 30,343) and a test set (n = 20,326). For the Lowlaavar models, 10,782 patients met the eligibility criteria, of whom 6175 were used to recalibrate the models and 4607 were used to test the performance of the adjusted model. The intercept of the recalibrated RISC-Malawi model was 0.12 (95% CI 0.07, 0.17), while the slope of the same model was 1.08 (95% CI 1.03, 1.13). The performance of the recalibrated models on the test set suggested that no model met the threshold of a perfectly calibrated model, which includes a calibration slope of 1 and a calibration-in-the-large/intercept of 0., Conclusions: Even after model adjustment, the calibration performances of the 4 models did not meet the recommended threshold for perfect calibration. This finding is suggestive of models over/underestimating the predicted risk of in-hospital mortality, potentially harmful clinically. Therefore, researchers may consider other alternatives, such as ensemble techniques to combine these models into a meta-model to improve out-of-sample predictive performance., (© 2023 The Authors. Paediatric and Perinatal Epidemiology published by John Wiley & Sons Ltd.)

Objective: Necrotizing enterocolitis (NEC) is an inflammatory disease of the gastrointestinal tract characterized by ischemic necrosis of the intestinal mucosa, mostly affecting premature neonates. Management of NEC includes medical care and surgical approaches, with supportive care and empirical antibiotic therapy recommended to avoid any disease progression. However, there is still no clear evidence-based consensus on empiric antibiotic strategies or surgical timing. This study was aimed to review the available evidence on the effectiveness and safety of different antibiotic regimens for NEC., Study Design: MEDLINE, EMBASE, Cochrane CENTRAL, and CINAHL databases were systematically searched through May 31, 2020. Randomized controlled trials (RCTs) and nonrandomized interventions reporting data on predefined outcomes related to NEC treatments were included. Clinical trials were assessed using the criteria and standard methods of the Cochrane risk of bias tool for randomized trials, while the risk of bias in nonrandomized studies of interventions was evaluated using the ROBINS-I tool. The certainty in evidence of each outcome's effects was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach., Results: Five studies were included in this review, two RCTs and three observational studies, for a total amount of 3,161 patients. One RCT compared the outcomes of parenteral (ampicillin plus gentamicin) and oral (gentamicin) treatment with parenteral only. Three studies (one RCT and two observational) evaluated adding anaerobic coverage to different parenteral regimens. The last observational study compared two different parenteral antibiotic combinations (ampicillin and gentamicin vs. cefotaxime and vancomycin)., Conclusion: No antimicrobial regimen has been shown to be superior to ampicillin and gentamicin in decreasing mortality and preventing clinical deterioration in NEC. The use of additional antibiotics providing anaerobic coverage, typically metronidazole, or use of other broad-spectrum regimens as first-line empiric therapy is not supported by the very limited current evidence. Well-conducted, appropriately sized comparative trials are needed to make evidence-based recommendations., Key Points: · Ampicillin and gentamicin are effective in decreasing mortality and preventing clinical deterioration in NEC.. · Metronidazole could be added in patients with surgical NEC.. · No study with high-quality evidence was found.., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: Missed nursing care undermines nursing standards of care and minimising this phenomenon is crucial to maintaining adequate patient safety and the quality of patient care. The concept is a neglected aspect of human resource for health thinking, and it remains understudied in low-income and middle-income country (LMIC) settings which have 90% of the global nursing workforce shortages. Our objective in this review was to document the prevalence of missed nursing care in LMIC, identify the categories of nursing care that are most missed and summarise the reasons for this., Methods: We conducted a systematic review searching Medline, Embase, Global Health, WHO Global index medicus and CINAHL from their inception up until August 2021. Publications were included if they were conducted in an LMIC and reported on any combination of categories, reasons and factors associated with missed nursing care within in-patient settings. We assessed the quality of studies using the Newcastle Ottawa Scale., Results: Thirty-one studies met our inclusion criteria. These studies were mainly cross-sectional, from upper middle-income settings and mostly relied on nurses' self-report of missed nursing care. The measurement tools used, and their reporting were inconsistent across the literature. Nursing care most frequently missed were non-clinical nursing activities including those of comfort and communication. Inadequate personnel numbers were the most important reasons given for missed care., Conclusions: Missed nursing care is reported for all key nursing task areas threatening care quality and safety. Data suggest nurses prioritise technical activities with more non-clinical activities missed, this undermines holistic nursing care. Improving staffing levels seems a key intervention potentially including sharing of less skilled activities. More research on missed nursing care and interventions to tackle it to improve quality and safety is needed in LMIC. PROSPERO registration number: CRD42021286897., (© 2023. The Author(s).)

Clinical audits are an important intervention that enables health workers to reflect on their practice and identify and act on modifiable gaps in the care provided. To effectively audit the quality of care provided to the small and sick newborns, the clinical audit process must use a structured tool that comprehensively covers the continuum of newborn care from immediately after birth to the period of newborn unit care. The objective of the study was to co-design a newborn clinical audit tool that considered the key principles of a Human Centred Design approach. A three-step Human Centred Design approach was used that began by (1) understanding the context, the users and the available audit tools through literature, focus group discussions and a consensus meeting that was used to develop a prototype audit tool and its implementation guide, (2) the prototype audit tool was taken through several cycles of reviewing with users on real cases in a high volume newborn unit and refining it based on their feedback, and (3) the final prototype tool and the implementation guide were then tested in two high volume newborn units to determine their usability. Several cycles of evaluation and redesigning of the prototype audit tool revealed that the users preferred a comprehensive tool that catered to human factors such as reduced free text for ease of filling, length of the tool, and aesthetics. Identified facilitators and barriers influencing the newborn clinical audit in Kenyan public hospitals informed the design of an implementation guide that builds on the strengths and overcomes the barriers. We adopted a Human Centred Design approach to developing a newborn clinical audit tool and an implementation guide that we believe are comprehensive and consider the characteristics of the context of use and the user requirements., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ogola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The objectives of this study were to (1)explore the quality of clinical data generated from hospitals providing in-patient neonatal care participating in a clinical information network (CIN) and whether data improved over time, and if data are adequate, (2)characterise accuracy of prescribing for basic treatments provided to neonatal in-patients over time. This was a retrospective cohort study involving neonates ≤28 days admitted between January 2018 and December 2021 in 20 government hospitals with an interquartile range of annual neonatal inpatient admissions between 550 and 1640 in Kenya. These hospitals participated in routine audit and feedback processes on quality of documentation and care over the study period. The study's outcomes were the number of patients as a proportion of all eligible patients over time with (1)complete domain-specific documentation scores, and (2)accurate domain-specific treatment prescription scores at admission, reported as incidence rate ratios. 80,060 neonatal admissions were eligible for inclusion. Upon joining CIN, documentation scores in the monitoring, other physical examination and bedside testing, discharge information, and maternal history domains demonstrated a statistically significant month-to-month relative improvement in number of patients with complete documentation of 7.6%, 2.9%, 2.4%, and 2.0% respectively. There was also statistically significant month-to-month improvement in prescribing accuracy after joining the CIN of 2.8% and 1.4% for feeds and fluids but not for Antibiotic prescriptions. Findings suggest that much of the variation observed is due to hospital-level factors. It is possible to introduce tools that capture important clinical data at least 80% of the time in routine African hospital settings but analyses of such data will need to account for missingness using appropriate statistical techniques. These data allow exploration of trends in performance and could support better impact evaluation, exploration of links between health system inputs and outcomes and scrutiny of variation in quality and outcomes of hospital care., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Tuti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: To identify nurse staffing and patient care outcome literature in published systematic reviews and map out the evidence gaps for low/middle-income countries (LMICs)., Methods: We included quantitative systematic reviews on nurse staffing levels and patient care outcomes in regular ward settings published in English. We excluded qualitative reviews or reviews on nursing skill mix. We searched the Cochrane Register of Systematic Reviews, the Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports, Medline, Embase and Cumulative Index to Nursing and Allied Health Literature from inception until July 2021. We used the A Measurement Tool to Assess Systematic Reviews -2 (AMSTAR-2) criteria for risk of bias assessment and conducted a narrative synthesis., Results: From 843 papers, we included 14 in our final synthesis. There were overlaps in primary studies summarised across reviews, but overall, the reviews summarised 136 unique primary articles. Only 4 out of 14 reviews had data on LMIC publications and only 9 (6.6%) of 136 unique primary articles were conducted in LMICs. Only 8 of 23 patient care outcomes were reported from LMICs. Less research was conducted in contexts with staffing levels that are typical of many LMIC contexts., Discussion: Our umbrella review identified very limited data for nurse staffing and patient care outcomes in LMICs. We also identified data from high-income countries might not be good proxies for LMICs as staffing levels where this research was conducted had comparatively better staffing levels than the few LMIC studies. This highlights a critical need for the conduct of nurse staffing research in LMIC contexts., Limitations: We included data on systematic reviews that scored low on our risk of bias assessment because we sought to provide a broad description of the research area. We only considered systematic reviews published in English and did not include any qualitative reviews in our synthesis., Prospero Registration Number: CRD42021286908., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Data from High Income Countries have now linked low nurse staff to patient ratios to poor quality patient care. Adequately staffing hospitals is however still a challenge in resource-constrained Low-middle income countries (LMICs) and poor staff-to-patient ratios are largely taken as a norm. This in part relates to limited evidence on the relationship between staffing and quality of patient care in these settings and also an absence of research on benefits that might occur from improving hospital staff numbers in LMICs. This study will determine the effect on the quality of patient care of prospectively adding extra nursing staff to newborn units in a resource constrained LMIC setting and describe the relationship between staffing and quality of care., Methods: This prospective workforce intervention study will involve a multi-method approach. We will conduct a before and after study in newborn units of 4 intervention hospitals and a single time-point comparison in 4 non-intervention hospitals to determine if there is a change in the level of missed nursing care, a process measure of the quality of patient care. We will also determine the effect of our intervention on routinely collected quality indicators using interrupted time series analysis. Using three nurse staffing metrics (Total nursing hours, nursing hours per patient day and nursing hours per patient per shift), we will describe the relationship between staffing and the quality of patient care., Discussion: There is an urgent need for the implementation of staffing policies in resource constrained LMICs that are guided by relevant contextual data. To the best of our knowledge, this is the first study to evaluate the prospective addition of nursing staff in resource-constrained care settings. Our findings are likely to provide the much-needed evidence for better staffing in these settings., Trial Registration: This study was retrospectively registered in the Pan African Clinical Trial Registry ( https://pactr.samrc.ac.za/Default.aspx?Logout=True ) database on the 10th of June 2022 with a unique identification number-PACTR202206477083141., (© 2022. The Author(s).)

Objective: Multidrug-resistant organisms (MDRO), especially carbapenem-resistant organisms (CRO), represent a threat for newborns. This study investigates the colonization prevalence of these pathogens in a newborn unit at a Kenyan tertiary hospital in an integrated approach combining routine microbiology, whole genome sequencing (WGS) and hospital surveillance data., Methods: The study was performed in the Kenyatta National Hospital (KNH) in 2019 over a four-month period and included 300 mother-baby pairs. A total of 1,097 swabs from newborns (weekly), mothers (once) and the hospital environment were taken. Routine clinical microbiology methods were applied for surveillance. Of the 288 detected MDRO, 160 isolates were analyzed for antimicrobial resistance genes and phylogenetic relatedness using whole genome sequencing (WGS) and bioinformatic analysis., Results: In maternal vaginal swabs, MDRO detection rate was 15% (n=45/300), including 2% CRO (n=7/300). At admission, MDRO detection rate for neonates was 16% (n=48/300), including 3% CRO (n=8/300) with a threefold increase for MDRO (44%, n=97/218) and a fivefold increase for CRO (14%, n=29/218) until discharge. Among CRO, K. pneumoniae harboring bla NDM-1 (n=20) or bla NDM-5 (n=16) were most frequent. WGS analysis revealed 20 phylogenetically related transmission clusters (including five CRO clusters). In environmental samples, the MDRO detection rate was 11% (n=18/164), including 2% CRO (n=3/164)., Conclusion: Our study provides a snapshot of MDRO and CRO in a Kenyan NBU. Rather than a large outbreak scenario, data indicate several independent transmission events. The CRO rate among newborns attributed to the spread of NDM-type carbapenemases is worrisome., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Villinger, Schultze, Musyoki, Inwani, Aluvaala, Okutoyi, Ziegler, Wieters, Stephan, Museve, Kempf and Masika.)

Background: Two neonatal mortality prediction models, the Neonatal Essential Treatment Score (NETS) which uses treatments prescribed at admission and the Score for Essential Neonatal Symptoms and Signs (SENSS) which uses basic clinical signs, were derived in high-mortality, low-resource settings to utilise data more likely to be available in these settings. In this study, we evaluate the predictive accuracy of two neonatal prediction models for all-cause in-hospital mortality., Methods: We used retrospectively collected routine clinical data recorded by duty clinicians at admission from 16 Kenyan hospitals used to externally validate and update the SENSS and NETS models that were initially developed from the data from the largest Kenyan maternity hospital to predict in-hospital mortality. Model performance was evaluated by assessing discrimination and calibration. Discrimination, the ability of the model to differentiate between those with and without the outcome, was measured using the c-statistic. Calibration, the agreement between predictions from the model and what was observed, was measured using the calibration intercept and slope (with values of 0 and 1 denoting perfect calibration)., Results: At initial external validation, the estimated mortality risks from the original SENSS and NETS models were markedly overestimated with calibration intercepts of - 0.703 (95% CI - 0.738 to - 0.669) and - 1.109 (95% CI - 1.148 to - 1.069) and too extreme with calibration slopes of 0.565 (95% CI 0.552 to 0.577) and 0.466 (95% CI 0.451 to 0.480), respectively. After model updating, the calibration of the model improved. The updated SENSS and NETS models had calibration intercepts of 0.311 (95% CI 0.282 to 0.350) and 0.032 (95% CI - 0.002 to 0.066) and calibration slopes of 1.029 (95% CI 1.006 to 1.051) and 0.799 (95% CI 0.774 to 0.823), respectively, while showing good discrimination with c-statistics of 0.834 (95% CI 0.829 to 0.839) and 0.775 (95% CI 0.768 to 0.782), respectively. The overall calibration performance of the updated SENSS and NETS models was better than any existing neonatal in-hospital mortality prediction models externally validated for settings comparable to Kenya., Conclusion: Few prediction models undergo rigorous external validation. We show how external validation using data from multiple locations enables model updating and improving their performance and potential value. The improved models indicate it is possible to predict in-hospital mortality using either treatments or signs and symptoms derived from routine neonatal data from low-resource hospital settings also making possible their use for case-mix adjustment when contrasting similar hospital settings., (© 2022. The Author(s).)

Background: Partners from an NGO, academia, industry and government applied a tool originating in the private sector - Quantitative Decision Making (QDM) - to rigorously assess whether to invest in testing a global health intervention. The proposed NEWBORN study was designed to assess whether topical emollient therapy with sunflower seed oil in infants with very low birthweight <1500 g in Kenya would result in a significant reduction in neonatal mortality compared to standard of care., Methods: The QDM process consisted of prior elicitation, modelling of prior distributions, and simulations to assess Probability of Success (PoS) via assurance calculations. Expert opinion was elicited on the probability that emollient therapy with sunflower seed oil will have any measurable benefit on neonatal mortality based on available evidence. The distribution of effect sizes was modelled and trial data simulated using Statistical Analysis System to obtain the overall assurance which represents the PoS for the planned study. A decision-making framework was then applied to characterise the ability of the study to meet pre-selected decision-making endpoints., Results: There was a 47% chance of a positive outcome (defined as a significant relative reduction in mortality of ≥15%), a 45% chance of a negative outcome (defined as a significant relative reduction in mortality <10%), and an 8% chance of ending in the consider zone (ie, a mortality reduction of 10 to <15%) for infants <1500 g., Conclusions: QDM is a novel tool from industry which has utility for prioritisation of investments in global health, complementing existing tools [eg, Child Health and Nutrition Research Initiative]. Results from application of QDM to the NEWBORN study suggests that it has a high probability of producing clear results. Findings encourage future formation of public-private partnerships for health., Competing Interests: Competing interests: AS, RAG, and LKK are current or former employees and shareholders of GlaxoSmithKline. SW, RM, AC, and LK are current or former employees of Save the Children. The authors have completed the ICMJE Declaration of Interest form (available upon request from the corresponding author), and declare no further conflicts of interest., (Copyright © 2022 by the Journal of Global Health. All rights reserved.)

Background: Medication errors are likely common in low- and middle-income countries (LMICs). In neonatal hospital care where the population with severe illness has a high mortality rate, around 14.9% of drug prescriptions have errors in LMICs settings. However, there is scant research on interventions to improve medication safety to mitigate such errors. Our objective is to improve routine neonatal care particularly focusing on effective prescribing practices with the aim of achieving reduced gentamicin medication errors., Methods: We propose to conduct an audit and feedback (A&F) study over 12 months in 20 hospitals with 12 months of baseline data. The medical and nursing leaders on their newborn units had been organised into a network that facilitates evaluating intervention approaches for improving quality of neonatal care in these hospitals and are receiving basic feedback generated from the baseline data. In this study, the network will (1) be expanded to include all hospital pharmacists, (2) include a pharmacist-only professional WhatsApp discussion group for discussing prescription practices, and (3) support all hospitals to facilitate pharmacist-led continuous medical education seminars on prescription practices at hospital level, i.e. default intervention package. A subset of these hospitals (n = 10) will additionally (1) have an additional hospital-specific WhatsApp group for the pharmacists to discuss local performance with their local clinical team, (2) receive detailed A&F prescription error reports delivered through mobile-based dashboard, and (3) receive a PDF infographic summarising prescribing performance circulated to the clinicians through the hospital-specific WhatsApp group, i.e. an extended package. Using interrupted time series analysis modelling changes in prescribing errors over time, coupled with process fidelity evaluation, and WhatsApp sentiment analysis, we will evaluate the success with which the A&F interventions are delivered, received, and acted upon to reduce prescribing error while exploring the extended package's success/failure relative to the default intervention package., Discussion: If effective, these theory-informed A&F strategies that carefully consider the challenges of LMICs settings will support the improvement of medication prescribing practices with the insights gained adapted for other clinical behavioural targets of a similar nature., Trial Registration: PACTR, PACTR202203869312307 . Registered 17th March 2022., (© 2022. The Author(s).)

Background : Adequate staffing is key to the delivery of nursing care and thus to improved inpatient and health service outcomes. Several systematic reviews have addressed the relationship between nurse staffing and these outcomes. Most primary studies within each systematic review are likely to be from high-income countries which have different practice contexts to low and middle-income countries (LMICs), although this has not been formally examined. We propose conducting an umbrella review to characterise the existing evidence linking nurse staffing to key outcomes and explicitly aim to identify evidence gaps in nurse staffing research in LMICs. Methods and analysis : This protocol was developed using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P). Literature searching will be conducted across Ovid Medline, Embase and EBSCO Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases. Two independent reviewers will conduct searching and data abstraction and discordance will be handled by discussion between both parties. The risk of bias of the individual studies will be performed using the AMSTAR-2 . Ethics and dissemination : Ethical permission is not required for this review as we will make use of already published data. We aim to publish the findings of our review in peer-reviewed journals. PROSPERO registration number: CRD42021286908., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Imam A et al.)

Background:   Missed nursing care (care left undone or task incompletion) is viewed as an important early predictor of adverse patient care outcomes and is a useful indicator to determine the quality of patient care. Available systematic reviews on missed nursing care are based mainly on primary studies from developed countries, and there is limited evidence on missed nursing care from low-middle income countries (LMICs). We propose conducting a systematic review to identify the magnitude of missed nursing care and document factors and reasons associated with this phenomenon in LMIC settings. Methods and analysis:   This protocol was developed using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P). We will conduct literature searching across the Ovid Medline, Embase and EBSCO Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases, from inception to 2021. Two independent reviewers will conduct searches and data abstraction, and discordance will be handled by discussion between both parties. The risk of bias of the individual studies will be determined using the Newcastle-Ottawa Scale (NOS). Ethics and dissemination : Ethical permission is not required for this review as we will make use of already published data. We aim to publish the findings of our review in peer-reviewed journals PROSPERO registration number: CRD42021286897 (27 th October 2021)., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Imam A et al.)

Background: Audit of facility-based care provided to small and sick newborns is a quality improvement initiative that helps to identify the modifiable gaps in newborn care (BMC Pregnancy Childbirth 14: 280, 2014). The aim of this work was to identify literature on modifiable factors in the care of newborns in the newborn units in health facilities in low-middle-income countries (LMICs). We also set out to design a measure of the quality of the perinatal and newborn audit process., Methods: The scoping review was conducted using the methodology outlined by Arksey and O'Malley and refined by Levac et al, (Implement Sci 5:1-9, 2010). We reported our results using the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. We identified seven factors to ensure a successful audit process based on World Health Organisation (WHO) recommendations which we subsequently used to develop a quality of audit process score., Data Sources: We conducted a structured search using PubMed, CINAHL, EMBASE, LILACS, POPLINE and African Index Medicus., Study Selection: Studies published in English between 1965 and December 2019 focusing on the identification of modifiable factors through clinical or mortality audits in newborn care in health facilities from LMICs., Data Extraction: We extracted data on the study characteristics, modifiable factors and quality of audit process indicators., Results: A total of six articles met the inclusion criteria. Of these, four were mortality audit studies and two were clinical audit studies that we used to assess the quality of the audit process. None of the studies were well conducted, two were moderately well conducted, and four were poorly conducted. The modifiable factors were divided into three time periods along the continuum of newborn care. The period of newborn unit care had the highest number of modifiable factors, and in each period, the health worker related modifiable factors were the most dominant., Conclusion: Based on the significant number of modifiable factors in the newborn unit, a neonatal audit tool is essential to act as a structured guide for auditing newborn unit care in LMICs. The quality of audit process guide is a useful method of ensuring high quality audits in health facilities., (© 2022. The Author(s).)

Background : Adequate staffing is key to the delivery of nursing care and thus to improved inpatient and health service outcomes. Several systematic reviews have addressed the relationship between nurse staffing and these outcomes. Most primary studies within each systematic review are likely to be from high-income countries which have different practice contexts to low and middle-income countries (LMICs), although this has not been formally examined. We propose conducting an umbrella review to characterise the existing evidence linking nurse staffing to key outcomes and explicitly aim to identify evidence gaps in nurse staffing research in LMICs. Methods and analysis : This protocol was developed using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P). Literature searching will be conducted across Ovid Medline, Embase and EBSCO Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases. Two independent reviewers will conduct searching and data abstraction and discordance will be handled by discussion between both parties. The risk of bias of the individual studies will be performed using the AMSTAR-2 . Ethics and dissemination : Ethical permission is not required for this review as we will make use of already published data. We aim to publish the findings of our review in peer-reviewed journals. PROSPERO registration number: CRD42021286908., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Imam A et al.)

Background:   Missed nursing care (care left undone or task incompletion) is viewed as an important early predictor of adverse patient care outcomes and is a useful indicator to determine the quality of patient care. Available systematic reviews on missed nursing care are based mainly on primary studies from developed countries, and there is limited evidence on missed nursing care from low-middle income countries (LMICs). We propose conducting a systematic review to identify the magnitude of missed nursing care and document factors and reasons associated with this phenomenon in LMIC settings. Methods and analysis:   This protocol was developed using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P). We will conduct literature searching across the Ovid Medline, Embase and EBSCO Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases, from inception to 2021. Two independent reviewers will conduct searches and data abstraction, and discordance will be handled by discussion between both parties. The risk of bias of the individual studies will be determined using the Newcastle-Ottawa Scale (NOS). Ethics and dissemination : Ethical permission is not required for this review as we will make use of already published data. We aim to publish the findings of our review in peer-reviewed journals PROSPERO registration number: CRD42021286897 (27 th October 2021)., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Imam A et al.)

Objectives: To characterise adoption and explore specific clinical and patient factors that might influence pulse oximetry and oxygen use in low-income and middle-income countries (LMICs) over time; to highlight useful considerations for entities working on programmes to improve access to pulse oximetry and oxygen., Design: A multihospital retrospective cohort study., Settings: All admissions (n=132 737) to paediatric wards of 18 purposely selected public hospitals in Kenya that joined a Clinical Information Network (CIN) between March 2014 and December 2020., Outcomes: Pulse oximetry use and oxygen prescription on admission; we performed growth-curve modelling to investigate the association of patient factors with study outcomes over time while adjusting for hospital factors., Results: Overall, pulse oximetry was used in 48.8% (64 722/132 737) of all admission cases. Use rose on average with each month of participation in the CIN (OR: 1.11, 95% CI 1.05 to 1.18) but patterns of adoption were highly variable across hospitals suggesting important factors at hospital level influence use of pulse oximetry. Of those with pulse oximetry measurement, 7% (4510/64 722) had hypoxaemia (SpO 2 <90%). Across the same period, 8.6% (11 428/132 737) had oxygen prescribed but in 87%, pulse oximetry was either not done or the hypoxaemia threshold (SpO 2 <90%) was not met. Lower chest-wall indrawing and other respiratory symptoms were associated with pulse oximetry use at admission and were also associated with oxygen prescription in the absence of pulse oximetry or hypoxaemia., Conclusion: The adoption of pulse oximetry recommended in international guidelines for assessing children with severe illness has been slow and erratic, reflecting system and organisational weaknesses. Most oxygen orders at admission seem driven by clinical and situational factors other than the presence of hypoxaemia. Programmes aiming to implement pulse oximetry and oxygen systems will likely need a long-term vision to promote adoption, guideline development and adherence and continuously examine impact., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Objectives: To examine the prevalence of dehydration without diarrhoea among admitted children aged 1-59 months and to describe fluid management practices in such cases., Design: A multisite observational study that used routine in-patient data collected prospectively between October 2013 and December 2018., Settings: Study conducted in 13 county referral hospitals in Kenya., Participants: Children aged 1-59 months with admission or discharge diagnosis of dehydration but had no diarrhoea as a symptom or diagnosis. Children aged <28 days and those with severe acute malnutrition were excluded., Results: The prevalence of dehydration in children without diarrhoea was 3.0% (2019/68 204) and comprised 15.9% (2019/12 702) of all dehydration cases. Only 55.8% (1127/2019) of affected children received either oral or intravenous fluid therapy. Where fluid treatment was given, the volumes, type of fluid, duration of fluid therapy and route of administration were similar to those used in the treatment of dehydration secondary to diarrhoea. Pneumonia (1021/2019, 50.6%) and malaria (715/2019, 35.4%) were the two most common comorbid diagnoses. Overall case fatality in the study population was 12.9% (260/2019)., Conclusion: Sixteen per cent of children hospitalised with dehydration do not have diarrhoea but other common illnesses. Two-fifths do not receive fluid therapy; a regimen similar to that used in diarrhoeal cases is used in cases where fluid is administered. Efforts to promote compliance with guidance in routine clinical settings should recognise special circumstances where guidelines do not apply, and further studies on appropriate management for dehydration in the absence of diarrhoea are required., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Most of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals., Methods: Continuously collected routine patients' data from structured paper record forms for all admissions to newborn units (NBUs) from 16 purposively selected Kenyan public hospitals that are part of a clinical information network were analysed together with data from all paediatric admissions ages 0-13 years from 14 of these hospitals. Data are used to show the proportion of all admissions and deaths in the neonatal age group and examine morbidity and mortality patterns, stratified by birth weight, and their variation across hospitals., Findings: During the 354 hospital months study period, 90 222 patients were admitted to the 14 hospitals contributing NBU and general paediatric ward data. 46% of all the admissions were neonates (aged 0-28 days), but they accounted for 66% of the deaths in the age group 0-13 years. 41 657 inborn neonates were admitted in the NBUs across the 16 hospitals during the study period. 4266/41 657 died giving a crude mortality rate of 10.2% (95% CI 9.97% to 10.55%), with 60% of these deaths occurring on the first-day of admission. Intrapartum-related complications was the single most common diagnosis among the neonates with birth weight of 2000 g or more who died. A threefold variation in mortality across hospitals was observed for birth weight categories 1000-1499 g and 1500-1999 g., Interpretation: The high proportion of neonatal deaths in hospitals may reflect changing patterns of childhood mortality. Majority of newborns died of preventable causes (>95%). Despite availability of high-impact low-cost interventions, hospitals have high and very variable mortality proportions after stratification by birth weight., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Objective: Prognostic models aid clinical decision making and evaluation of hospital performance. Existing neonatal prognostic models typically use physiological measures that are often not available, such as pulse oximetry values, in routine practice in low-resource settings. We aimed to develop and validate two novel models to predict all cause in-hospital mortality following neonatal unit admission in a low-resource, high-mortality setting., Study Design and Setting: We used basic, routine clinical data recorded by duty clinicians at the time of admission to derive (n=5427) and validate (n=1627) two novel models to predict in-hospital mortality. The Neonatal Essential Treatment Score (NETS) included treatments prescribed at the time of admission while the Score for Essential Neonatal Symptoms and Signs (SENSS) used basic clinical signs. Logistic regression was used, and performance was evaluated using discrimination and calibration., Results: At derivation, c-statistic (discrimination) for NETS was 0.92 (95% CI 0.90 to 0.93) and that for SENSS was 0.91 (95% CI 0.89 to 0.93). At external (temporal) validation, NETS had a c-statistic of 0.89 (95% CI 0.86 to 0.92) and SENSS 0.89 (95% CI 0.84 to 0.93). The calibration intercept for NETS was -0.72 (95% CI -0.96 to -0.49) and that for SENSS was -0.33 (95% CI -0.56 to -0.11)., Conclusion: Using routine neonatal data in a low-resource setting, we found that it is possible to predict in-hospital mortality using either treatments or signs and symptoms. Further validation of these models may support their use in treatment decisions and for case-mix adjustment to help understand performance variation across hospitals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Healthcare systems across the world and especially those in low-resource settings (LRS) are under pressure and one of the first priorities must be to prevent any harm done while trying to deliver care. Health care workers, especially department leaders, need the diagnostic abilities to identify local safety concerns and design actions that benefit their patients. We draw on concepts from the safety sciences that are less well-known than mainstream quality improvement techniques in LRS. We use these to illustrate how to analyse the complex interactions between resources and tools, the organisation of tasks and the norms that may govern behaviours, together with the strengths and vulnerabilities of systems. All interact to influence care and outcomes. To employ these techniques leaders will need to focus on the best attainable standards of care, build trust and shift away from the blame culture that undermines improvement. Health worker education should include development of the technical and relational skills needed to perform these system diagnostic roles. Some safety challenges need leadership from professional associations to provide important resources, peer support and mentorship to sustain safety work., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

We have worked to develop a Clinical Information Network (CIN) in Kenya as an early form of learning health systems (LHS) focused on paediatric and neonatal care that now spans 22 hospitals. CIN's aim was to examine important outcomes of hospitalisation at scale, identify and ultimately solve practical problems of service delivery, drive improvements in quality and test interventions. By including multiple routine settings in research, we aimed to promote generalisability of findings and demonstrate potential efficiencies derived from LHS. We illustrate the nature and range of research CIN has supported over the past 7 years as a form of LHS. Clinically, this has largely focused on common, serious paediatric illnesses such as pneumonia, malaria and diarrhoea with dehydration with recent extensions to neonatal illnesses. CIN also enables examination of the quality of care, for example that provided to children with severe malnutrition and the challenges encountered in routine settings in adopting simple technologies (pulse oximetry) and more advanced diagnostics (eg, Xpert MTB/RIF). Although regular feedback to hospitals has been associated with some improvements in quality data continue to highlight system challenges that undermine provision of basic, quality care (eg, poor access to blood glucose testing and routine microbiology). These challenges include those associated with increased mortality risk (eg, delays in blood transfusion). Using the same data the CIN platform has enabled conduct of randomised trials and supports malaria vaccine and most recently COVID-19 surveillance. Employing LHS principles has meant engaging front-line workers, clinical managers and national stakeholders throughout. Our experience suggests LHS can be developed in low and middle-income countries that efficiently enable contextually appropriate research and contribute to strengthening of health services and research systems., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

In low and middle-income countries (LMIC) general hospitals are important for delivering some key acute care services. Neonatal care is emblematic of these acute services as averting deaths requires skilled care over many days from multiple professionals with at least basic equipment. However, hospital care is often of poor quality and large-scale change is needed to improve outcomes. In this manuscript we aim to show how we have drawn upon our understanding of contexts of care in Kenyan general hospital NBUs, and on social and behavioural theories that offer potential mechanisms of change in these settings, to develop an initial programme theory guiding a large scale change intervention to improve neonatal care and outcomes.  Our programme theory is an expression of our assumptions about what actions will be both useful and feasible.  It incorporates a recognition of our strengths and limitations as a research-practitioner partnership to influence change. The steps we employ represent the initial programme theory development phase commonly undertaken in many Realist Evaluations. However, unlike many Realist Evaluations that develop initial programme theories focused on pre-existing interventions or programmes, our programme theory informs the design of a new intervention that we plan to execute. Within this paper we articulate briefly how we propose to operationalise this new intervention. Finally, we outline the quantitative and qualitative research activities that we will use to address specific questions related to the delivery and effects of this new intervention, discussing some of the challenges of such study designs. We intend that this research on the intervention will inform future efforts to revise the programme theory and yield transferable learning., Competing Interests: Competing interests: All authors are supported by research funding for work in fields related to the topic of this manuscript, have been involved in early phases of developing the Kenyan Clinical Information Network or are members of organisations referred to in this report such as the Kenya Paediatric Association and the Kenya research team undertaking ongoing work on neonatal care., (Copyright: © 2020 English M et al.)

Objectives: To identify and appraise the methodological rigour of multivariable prognostic models predicting in-hospital paediatric mortality in low-income and middle-income countries (LMICs)., Design: Systematic review of peer-reviewed journals., Data Sources: MEDLINE, CINAHL, Google Scholar and Web of Science electronic databases since inception to August 2019., Eligibility Criteria: We included model development studies predicting in-hospital paediatric mortality in LMIC., Data Extraction and Synthesis: This systematic review followed the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies framework. The risk of bias assessment was conducted using Prediction model Risk of Bias Assessment Tool (PROBAST). No quantitative summary was conducted due to substantial heterogeneity that was observed after assessing the studies included., Results: Our search strategy identified a total of 4054 unique articles. Among these, 3545 articles were excluded after review of titles and abstracts as they covered non-relevant topics. Full texts of 509 articles were screened for eligibility, of which 15 studies reporting 21 models met the eligibility criteria. Based on the PROBAST tool, risk of bias was assessed in four domains; participant, predictors, outcome and analyses. The domain of statistical analyses was the main area of concern where none of the included models was judged to be of low risk of bias., Conclusion: This review identified 21 models predicting in-hospital paediatric mortality in LMIC. However, most reports characterising these models are of poor quality when judged against recent reporting standards due to a high risk of bias. Future studies should adhere to standardised methodological criteria and progress from identifying new risk scores to validating or adapting existing scores., Prospero Registration Number: CRD42018088599., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Background Increasing numbers of neonates are undergoing painful procedures in low-income and middle-income countries, with adequate analgesia seldom used. In collaboration with a multi-disciplinary team in Kenya, we aimed to establish the first evidence-based guidelines for the management of routine procedure-related neonatal pain that consider low-resource hospital settings., Methods: We did a systematic review by searching MEDLINE, Embase, CINAHL, and CENTRAL databases for studies published from Jan 1, 1953, to March 31, 2019. We included data from randomised controlled trials using heart rate, oxygen saturation (SpO 2 ), premature infant pain profile (PIPP) score, neonatal infant pain scale (NIPS) score, neonatal facial coding system score, and douleur aiguë du nouveau-né scale score as pain outcome measures. We excluded studies in which neonates were undergoing circumcision or were intubated, studies from which data were unextractable, or when pain was scored by non-trained individuals. We did a narrative synthesis of all studies, and meta-analysis when data were available from multiple studies comparing the same analgesics and controls and using the same outcome measures. 17 Kenyan health-care professionals formed our clinical guideline development panel, and we used the Grading of Recommendations, Assessment, Development and Evaluation framework and the panel's knowledge of the local health-care context to guide the guideline development process. This study is registered with PROSPERO, CRD42019126620., Findings: Of 2782 studies assessed for eligibility, data from 149 (5%) were analysed, with 80 (3%) of these further contributing to our meta-analysis. We found a high level of certainty for the superiority of breastfeeding over placebo or no intervention (standardised mean differences [SMDs] were -1·40 [95% CI -1·96 to -0·84] in PIPP score and -2·20 [-2·91 to -1·48] in NIPS score), and the superiority of oral sugar solutions over placebo or no intervention (SMDs were -0·38 [-0·61 to -0·16] in heart rate and 0·23 [0·04 to 0·42] in SpO 2 ). We found a moderate level of certainty for the superiority for expressed breastmilk over placebo or no intervention (SMDs were -0·46 [95% CI -0·87 to -0·05] in heart rate and 0·48 [0·20 to 0·75] in SpO 2 ). Therefore, the panel recommended that breastfeeding should be given as first-line analgesic treatment, initiated at least 2 min pre-procedure. Given contextual factors, for neonates who are unable to breastfeed, 1-2 mL of expressed breastmilk should be given as first-line analgesic, or 1-2 mL of oral sugar (≥10% concentration) as second-line analgesic. The panel also recommended parental presence during procedures with adjunctive provision of skin-to-skin care, or non-nutritive sucking when possible., Interpretation: We have generated Kenya's first neonatal analgesic guidelines for routine procedures, which have been adopted by the Kenyan Ministry of Health, and have shown a framework for clinical guideline development that is applicable to other low-income and middle-income health-care settings., Funding: Wellcome Trust Research Programme, and the Africa-Oxford Initiative., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: In low- and middle-income countries (LMICs) where healthcare resources are often limited, making decisions on appropriate treatment choices is critical in ensuring reduction of paediatric deaths as well as instilling proper utilisation of the already constrained healthcare resources. Well-developed and validated prognostic models can aid in early recognition of potential risks thus contributing to the reduction of mortality rates. The aim of the planned systematic review is to identify and appraise the methodological rigor of multivariable prognostic models predicting in-hospital paediatric mortality in LMIC in order to identify statistical and methodological shortcomings deserving special attention and to identify models for external validation. Methods and analysis: This protocol has followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols. A search of articles will be conducted in MEDLINE, Google Scholar, and CINAHL (via EbscoHost) from inception to 2019 without any language restriction. We will also perform a search in Web of Science to identify additional reports that cite the identified studies. Data will be extracted from relevant articles in accordance with the Cochrane Prognosis Methods' guidance; the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies. Methodological quality assessment will be performed based on prespecified domains of the Prediction study Risk of Bias Assessment Tool. Ethics and dissemination: Ethical permission will not be required as this study will use published data. Findings from this review will be shared through publication in peer-reviewed scientific journals and, presented at conferences. It is our hope that this study will contribute to the development of robust multivariable prognostic models predicting in-hospital paediatric mortality in low- and middle-income countries. Registration: PROSPERO ID CRD42018088599; registered on 13 February 2018., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Ogero M et al.)

Introduction: Neonatal mortality is an urgent policy priority to improve global population health and reduce health inequality. As health systems in Kenya and elsewhere seek to tackle increased neonatal mortality by improving the quality of care, one option is to train and employ neonatal healthcare assistants (NHCAs) to support professional nurses by taking up low-skill tasks., Methods: Monte-Carlo simulation was performed to estimate the potential impact of introducing NHCAs in neonatal nursing care in four public hospitals in Nairobi on effectively treated newborns and staff costs over a period of 10 years. The simulation was informed by data from 3 workshops with >10 stakeholders each, hospital records and scientific literature. Two univariate sensitivity analyses were performed to further address uncertainty., Results: Stakeholders perceived that 49% of a nurse full-time equivalent could be safely delegated to NHCAs in standard care, 31% in intermediate care and 20% in intensive care. A skill-mix with nurses and NHCAs would require ~2.6 billionKenyan Shillings (KES) (US$26 million) to provide quality care to 58% of all newborns in need (ie, current level of coverage in Nairobi) over a period of 10 years. This skill-mix configuration would require ~6 billion KES (US$61 million) to provide quality of care to almost all newborns in need over 10 years., Conclusion: Changing skill-mix in hospital care by introducing NHCAs may be an affordable way to reduce neonatal mortality in low/middle-income countries. This option should be considered in ongoing policy discussions and supported by further evidence., Competing Interests: Competing interests: ME reports grants from Wellcome Trust/UK-MRC/DFID/ESRC, during the conduct of the study., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.)

Introduction: There were almost 1 million deaths in children aged between 5 and 14 years in 2017, and pneumonia accounted for 11%. However, there are no validated guidelines for pneumonia management in older children and data to support their development are limited. We sought to understand risk factors for mortality among children aged 5-14 years hospitalised with pneumonia in district-level health facilities in Kenya., Methods: We did a retrospective cohort study using data collected from an established clinical information network of 13 hospitals. We reviewed records for children aged 5-14 years admitted with pneumonia between 1 March 2014 and 28 February 2018. Individual clinical signs were examined for association with inpatient mortality using logistic regression. We used existing WHO criteria (intended for under 5s) to define levels of severity and examined their performance in identifying those at increased risk of death., Results: 1832 children were diagnosed with pneumonia and 145 (7.9%) died. Severe pallor was strongly associated with mortality (adjusted OR (aOR) 8.06, 95% CI 4.72 to 13.75) as were reduced consciousness, mild/moderate pallor, central cyanosis and older age (>9 years) (aOR >2). Comorbidities HIV and severe acute malnutrition were also associated with death (aOR 2.31, 95% CI 1.39 to 3.84 and aOR 1.89, 95% CI 1.12 to 3.21, respectively). The presence of clinical characteristics used by WHO to define severe pneumonia was associated with death in univariate analysis (OR 2.69). However, this combination of clinical characteristics was poor in discriminating those at risk of death (sensitivity: 0.56, specificity: 0.68, and area under the curve: 0.62)., Conclusion: Children >5 years have high inpatient pneumonia mortality. These findings also suggest that the WHO criteria for classification of severity for children under 5 years do not appear to be a valid tool for risk assessment in this older age group, indicating the urgent need for evidence-based clinical guidelines for this neglected population., Competing Interests: Competing interests: None declared.

Delivery in a health facility is a key strategy for reducing maternal and neonatal mortality, yet increasing use of facilities has not consistently translated into reduced mortality in low- and middle-income countries. In such countries, many deliveries occur at primary care facilities, where the quality of care is poor. We modeled the geographic feasibility of service delivery redesign that shifted deliveries from primary care clinics to hospitals in six countries: Haiti, Kenya, Malawi, Namibia, Nepal, and Tanzania. We estimated the proportion of women within two hours of the nearest delivery facility, both currently and under redesign. Today, 83-100 percent of pregnant women in the study countries have two-hour access to a delivery facility. A policy of redesign would reduce two-hour access by at most 10 percent, ranging from 0.6 percent in Malawi to 9.9 percent in Tanzania. Relocating delivery services to hospitals would not unduly impede geographic access to care in the study countries. This policy should be considered in low- and middle-income countries, as it may be an effective approach to reducing maternal and newborn deaths.

Background: Clinical outcomes data are a crucial component of efforts to improve health systems globally. Strengthening of these health systems is essential if the Sustainable Development Goals (SDG) are to be achieved. Target 3.2 of SDG Goal 3 is to end preventable deaths and reduce neonatal mortality to 12 per 1,000 or lower by 2030. There is a paucity of data on neonatal in-hospital mortality in Kenya that is poorly captured in the existing health information system. Better measurement of neonatal mortality in facilities may help promote improvements in the quality of health care that will be important to achieving SDG 3 in countries such as Kenya. Methods: This was a cohort study using routinely collected data from a large urban neonatal unit in Nairobi, Kenya. All the patients admitted to the unit between April 2014 to December 2015 were included. Clinical characteristics are summarised descriptively, while the competing risk method was used to estimate the probability of in-hospital mortality considering discharge alive as the competing risk. Results: A total of 9,115 patients were included. Most were males (966/9115, 55%) and the majority (6287/9115, 69%) had normal birthweight (2.5 to 4 kg). Median length of stay was 2 days (range, 0 to 98 days) while crude mortality was 9.2% (839/9115). The probability of in-hospital death was higher than discharge alive for birthweight less than 1.5 kg with the transition to higher probability of discharge alive observed after the first week in birthweight 1.5 to <2 kg. Conclusions: These prognostic data may inform decision making, e.g. in the organisation of neonatal in-patient service delivery to improve the quality of care. More of such data are therefore required from neonatal units in Kenya and other low resources settings especially as more advanced neonatal care is scaled up., Competing Interests: No competing interests were disclosed.

Neonatal deaths contribute a growing proportion to childhood mortality, and increasing access to inpatient newborn care has been identified as a potential driver of improvements in child health. However, previous work by this research team identified substantial gaps in the coverage and standardisation of inpatient newborn care in Nairobi City County, Kenya. To address the issue in this particular setting, we sought to draft recommendations on the categorisation of neonatal inpatient services through a process of policy review, evidence collation and examination of guidance in other countries. This work supported discussions by a panel of local experts representing a diverse set of stakeholders, who focused on formulating pragmatic, context-relevant guidance. Experts in the discussions rapidly agreed on overarching priorities guiding their decision-making, and that three categories of inpatient neonatal care (standard, intermediate and intensive care) were appropriate. Through a modified nominal group technique, they achieved consensus on allocating 36 of the 38 proposed services to these categories and made linked recommendations on minimum healthcare worker requirements (skill mix and staff numbers). This process was embedded in the local context where the need had been identified, and required only modest resources to produce recommendations on the categorisation of newborn inpatient care that the experts agreed could be relevant in other Kenyan settings. Recommendations prioritised the strengthening of existing facilities linked to a need to develop effective referral systems. In particular, expansion of access to the standard category of inpatient neonatal care was recommended. The process and the agreed categorisations could inform discussion in other low-resource settings seeking to address unmet needs for inpatient neonatal care., Competing Interests: Competing interests: ME advises the Kenyan Paediatric Association and sits on the Ministry of Health (Kenya) Advisory Group.

Essential interventions to reduce neonatal deaths that can be effectively delivered in hospitals have been identified. Improving information systems may support routine monitoring of the delivery of these interventions and outcomes at scale. We used cycles of audit and feedback (A&F) coupled with the use of a standardised newborn admission record (NAR) form to explore the potential for creating a common inpatient neonatal data platform and illustrate its potential for monitoring prescribing accuracy. Revised NARs were introduced in a high volume, neonatal unit in Kenya together with 13 A&F meetings over a period of 3  years from January 2014 to November 2016. Data were abstracted from medical records for 15 months before introduction of the revised NAR and A&F and during the 3 years of A&F. We calculated, for each patient, the percentage of documented items from among the total recommended for documentation and trends calculated over time. Gentamicin prescribing accuracy was also tracked over time. Records were examined for 827 and 7336 patients in the pre-A&F and post-A&F periods, respectively. Documentation scores improved overall. Documentation of gestational age improved from <15% in 2014 to >75% in 2016. For five recommended items, including temperature, documentation remained <50%. 16.7% (n=1367; 95%  CI 15.9 to 17.6) of the admitted babies had a diagnosis of neonatal sepsis needing antibiotic treatment. In this group, dosing accuracy of gentamicin improved over time for those under 2  kg from 60% (95%36.1 to 80.1) in 2013 to 83% (95% CI 69.2 to 92.3) in 2016. We report that it is possible to improve routine data collection in neonatal units using a standardised neonatal record linked to relatively basic electronic data collection tools and cycles of A&F. This can be useful in identifying potential gaps in care and tracking outcomes with an aim of improving the quality of care., Competing Interests: Competing interests: None declared.

Background: Effective coverage requires that those in need can access skilled care supported by adequate resources. There are, however, few studies of effective coverage of facility-based neonatal care in low-income settings, despite the recognition that improving newborn survival is a global priority., Methods: We used a detailed retrospective review of medical records for neonatal admissions to public, private not-for-profit (mission) and private-for-profit (private) sector facilities providing 24×7 inpatient neonatal care in Nairobi City County to estimate the proportion of small and sick newborns receiving nationally recommended care across six process domains. We used our findings to explore the relationship between facility measures of structure and process and estimate effective coverage., Results: Of 33 eligible facilities, 28 (four public, six mission and 18 private), providing an estimated 98.7% of inpatient neonatal care in the county, agreed to partake. Data from 1184 admission episodes were collected. Overall performance was lowest (weighted mean score 0.35 [95% confidence interval or CI: 0.22-0.48] out of 1) for correct prescription of fluid and feed volumes and best (0.86 [95% CI: 0.80-0.93]) for documentation of demographic characteristics. Doses of gentamicin, when prescribed, were at least 20% higher than recommended in 11.7% cases. Larger (often public) facilities tended to have higher process and structural quality scores compared with smaller, predominantly private, facilities. We estimate effective coverage to be 25% (estimate range: 21-31%). These newborns received high-quality inpatient care, while almost half (44.5%) of newborns needed care but did not receive it and a further 30.4% of newborns received an inadequate service., Conclusions: Failure to receive services and gaps in quality of care both contribute to a shortfall in effective coverage in Nairobi City County. Three-quarters of small and sick newborns do not have access to high-quality facility-based care. Substantial improvements in effective coverage will be required to tackle high neonatal mortality in this urban setting with high levels of poverty.

Aim: There are 2.7 million neonatal deaths annually, 75% of which occur in sub-Saharan Africa and South Asia. Effective treatment of hypoxaemia through tailored oxygen therapy could reduce neonatal mortality and prevent oxygen toxicity., Methods: We undertook a two-part prospective study of neonates admitted to a neonatal unit in Nairobi, Kenya, between January and December 2015. We determined the prevalence of hypoxaemia and explored associations of clinical risk factors and signs of respiratory distress with hypoxaemia and mortality. After staff training on oxygen saturation (SpO 2 ) target ranges, we enrolled a consecutive sample of neonates admitted for oxygen and measured SpO 2 at 0, 6, 12, 18 and 24 h post-admission. We estimated the proportion of neonates outside the target range (≥34 weeks: ≥92%; <34 weeks: 89-93%) with 95% confidence intervals (CIs)., Results: A total of 477 neonates were enrolled. Prevalence of hypoxaemia was 29.2%. Retractions (odds ratio (OR) 2.83, 95% CI 1.47-5.47), nasal flaring (OR 2.68, 95% CI 1.51-4.75), and grunting (OR 2.47, 95% CI 1.27-4.80) were significantly associated with hypoxaemia. Nasal flaring (OR 2.85, 95% CI 1.25-6.54), and hypoxaemia (OR 3.06, 95% CI 1.54-6.07) were significantly associated with mortality; 64% of neonates receiving oxygen were out of range at ≥2 time points and 43% at ≥3 time points., Conclusion: There is a high prevalence of hypoxaemia at admission and a strong association between hypoxaemia and mortality in this Kenyan neonatal unit. Many neonates had out of range SpO 2 values while receiving oxygen. Further research is needed to test strategies aimed at improving the accuracy of oxygen provision in low-resource settings., (© 2017 The Authors Journal of Paediatrics and Child Health published by John Wiley & Sons Australia, Ltd on behalf of Paediatrics and Child Health Division (The Royal Australasian College of Physicians).)

Background: Treatment intensity scores can predict mortality and estimate resource use. They may therefore be of interest for essential neonatal care in low resource settings where neonatal mortality remains high. We sought to systematically review neonatal treatment intensity scores to (1) assess the level of evidence on predictive performance in predicting clinical outcomes and estimating resource utilisation and (2) assess the applicability of the identified models to decision making for neonatal care in low resource settings., Methods: We conducted a systematic search of PubMed, EMBASE (OVID), CINAHL, Global Health Library (Global index, WHO) and Google Scholar to identify studies published up until 21 December 2016. Included were all articles that used treatments as predictors in neonatal models. Individual studies were appraised using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). In addition, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used as a guiding framework to assess certainty in the evidence for predicting outcomes across studies., Results: Three thousand two hundred forty-nine articles were screened, of which ten articles were included in the review. All of the studies were conducted in neonatal intensive care units with sample sizes ranging from 22 to 9978, with a median of 163. Two articles reported model development, while eight reported external application of existing models to new populations. Meta-analysis was not possible due heterogeneity in the conduct and reporting of the identified studies. Discrimination as assessed by area under receiver operating characteristic curve was reported for in-hospital mortality, median 0.84 (range 0.75-0.96, three studies), early adverse outcome and late adverse outcome (0.78 and 0.59, respectively, one study)., Conclusion: Existing neonatal treatment intensity models show promise in predicting mortality and morbidity. There is however low certainty in the evidence on their performance in essential neonatal care in low resource settings as all studies had methodological limitations and were conducted in intensive care. The approach may however be developed further for low resource settings like Kenya because treatment data may be easier to obtain compared to measures of physiological status., Systematic Review Registration: PROSPERO CRD42016034205.

There are minimal data to define normal oxygen saturation (SpO 2 ) levels for infants within the first 24 hours of life and even fewer data generalisable to the 7% of the global population that resides at an altitude of >1500 m. The aim of this study was to establish the reference range for SpO 2 in healthy term and preterm neonates within 24 hours in Nairobi, Kenya, located at 1800 m. A random sample of clinically well infants had SpO 2 measured once in the first 24 hours. A total of 555 infants were enrolled. The 5th-95th percentile range for preductal and postductal SpO 2 was 89%-97% for the term and normal birthweight groups, and 90%-98% for the preterm and low birthweight (LBW) groups. This may suggest that 89% and 97% are reasonable SpO 2 bounds for well term, preterm and LBW infants within 24 hours at an altitude of 1800 m., Competing Interests: Competing interestsNone declared., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Introduction: Progress has been made in Kenya towards reducing child mortality as part of efforts aligned with the fourth Millennium Development Goal. However, little advancement has been made in reducing mortality among newborns, which now accounts for 45% of all child deaths. The frequently unanticipated nature of neonatal illness, its severity and the high dependency of sick newborns on skilled care make the provision of inpatient hospital services one key component of strategies to improve newborn survival., Methods and Analyses: This project aims to assess the availability and quality of inpatient newborn care in hospitals in Nairobi City County across the public, private and not-for-profit sectors and align this to the estimated need for such services, providing a description of the quantity and quality gaps between capacity and demand. The population level burden of disease will be estimated using morbidity incidence estimates from a literature review applied to subcounty estimates of population-adjusted births, providing a spatially disaggregated estimate of need within the county. This will be followed by a survey of neonatal services across all health facilities providing 24/7 inpatient newborn care in the county. The survey will include: a retrospective audit of admission registers to estimate the usage of facilities and case-mix of patients; a structural assessment of facilities to gain insight into capacity; a questionnaire to nursing staff focusing on the process of delivering key obstetric and neonatal interventions; and a retrospective case audit to assess adherence to guidelines by clinicians., Ethics and Dissemination: This study has been approved by the Kenya Medical Research Institute Scientific and Ethics Review Unit (SSC protocol No.2999). Results will be disseminated: to participating facilities through individualised reports and a joint workshop; to local and national stakeholders through meetings and a summary report; and to the international community through peer-review publication and international meetings., Competing Interests: Conflicts of Interest: None declared., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)