Comprehensive assessment of pediatric acute and inpatient care at a tertiary referral hospital in Malawi: opportunities for quality improvement.

BACKGROUND: Despite the reduction in global under-5 mortality over the last decade, childhood deaths remain high. To combat this, there has been a shift in focus from disease-specific interventions to use of healthcare data for resource allocation, evaluation of performance and impact, and accountability. This is a descriptive analysis of data derived from a prospective cohort study describing paediatric admissions to a tertiary referral hospital in Malawi for the purpose of process evaluation and quality improvement. METHODS: Using a REDCap database, we collected data for patients admitted acutely to Kamuzu Central Hospital, a tertiary referral centre in the central region. Data were collected from 17 123 paediatric inpatients from 2017 to 2020. RESULTS: Approximately 6% of patients presented with either two or more danger signs or severely abnormal vital signs. Infants less than 6 months, who had the highest mortality rate, were also the most critically ill on arrival to the hospital. Sepsis was diagnosed in about 20% of children across all age groups. Protocols for the management of high-volume, lower-acuity conditions such as uncomplicated malaria and pneumonia were generally well adhered to, but there was a low rate of completion for labs, radiology studies and subspecialty consultations required to provide care for high acuity or complex conditions. The overall mortality rate was 4%, and 60% of deaths occurred within the first 48 hours of admission. CONCLUSION: Our data highlight the need to improve the quality of care provided at this tertiary-level centre by focusing on the initial stabilisation of high-acuity patients and augmenting resources to provide comprehensive care. This may include capacity building through the training of specialists, implementation of clinical processes, provision of specialised equipment and increasing access to and reliability of ancillary services. Data collection, analysis and routine use in policy and decision-making must be a pillar on which improvement is built.

Health facility assessment of small and sick newborn care in low- and middle-income countries: systematic tool development and operationalisation with NEST360 and UNICEF.

BACKGROUND: Each year an estimated 2.3 million newborns die in the first 28 days of life. Most of these deaths are preventable, and high-quality neonatal care is fundamental for surviving and thriving. Service readiness is used to assess the capacity of hospitals to provide care, but current health facility assessment (HFA) tools do not fully evaluate inpatient small and sick newborn care (SSNC). METHODS: Health systems ingredients for SSNC were identified from international guidelines, notably World Health Organization (WHO), and other standards for SSNC. Existing global and national service readiness tools were identified and mapped against this ingredients list. A novel HFA tool was co-designed according to a priori considerations determined by policymakers from four African governments, including that the HFA be completed in one day and assess readiness across the health system. The tool was reviewed by > 150 global experts, and refined and operationalised in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania between September 2019 and March 2021. RESULTS: Eight hundred and sixty-six key health systems ingredients for service readiness for inpatient SSNC were identified and mapped against four global and eight national tools measuring SSNC service readiness. Tools revealed major content gaps particularly for devices and consumables, care guidelines, and facility infrastructure, with a mean of 13.2% (n = 866, range 2.2-34.4%) of ingredients included. Two tools covered 32.7% and 34.4% (n = 866) of ingredients and were used as inputs for the new HFA tool, which included ten modules organised by adapted WHO health system building blocks, including: infrastructure, pharmacy and laboratory, medical devices and supplies, biomedical technician workshop, human resources, information systems, leadership and governance, family-centred care, and infection prevention and control. This HFA tool can be conducted at a hospital by seven assessors in one day and has been used in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania. CONCLUSION: This HFA tool is available open-access to adapt for use to comprehensively measure service readiness for level-2 SSNC, including respiratory support. The resulting facility-level data enable comparable tracking for Every Newborn Action Plan coverage target four within and between countries, identifying facility and national-level health systems gaps for action.

Quantifying health facility service readiness for small and sick newborn care: comparing standards-based and WHO level-2 + scoring for 64 hospitals implementing with NEST360 in Kenya, Malawi, Nigeria, and Tanzania.

BACKGROUND: Service readiness tools are important for assessing hospital capacity to provide quality small and sick newborn care (SSNC). Lack of summary scoring approaches for SSNC service readiness means we are unable to track national targets such as the Every Newborn Action Plan targets. METHODS: A health facility assessment (HFA) tool was co-designed by Newborn Essential Solutions and Technologies (NEST360) and UNICEF with four African governments. Data were collected in 68 NEST360-implementing neonatal units in Kenya, Malawi, Nigeria, and Tanzania (September 2019-March 2021). Two summary scoring approaches were developed: a) standards-based, including items for SSNC service readiness by health system building block (HSBB), and scored on availability and functionality, and b) level-2 + , scoring items on readiness to provide WHO level-2 + clinical interventions. For each scoring approach, scores were aggregated and summarised as a percentage and equally weighted to obtain an overall score by hospital, HSBB, and clinical intervention. RESULTS: Of 1508 HFA items, 1043 (69%) were included in standards-based and 309 (20%) in level-2 + scoring. Sixty-eight neonatal units across four countries had median standards-based scores of 51% [IQR 48-57%] at baseline, with variation by country: 62% [IQR 59-66%] in Kenya, 49% [IQR 46-51%] in Malawi, 50% [IQR 42-58%] in Nigeria, and 55% [IQR 53-62%] in Tanzania. The lowest scoring was family-centred care [27%, IQR 18-40%] with governance highest scoring [76%, IQR 71-82%]. For level-2 + scores, the overall median score was 41% [IQR 35-51%] with variation by country: 50% [IQR 44-53%] in Kenya, 41% [IQR 35-50%] in Malawi, 33% [IQR 27-37%] in Nigeria, and 41% [IQR 32-52%] in Tanzania. Readiness to provide antibiotics by culture report was the highest-scoring intervention [58%, IQR 50-75%] and neonatal encephalopathy management was the lowest-scoring [21%, IQR 8-42%]. In both methods, overall scores were low (< 50%) for 27 neonatal units in standards-based scoring and 48 neonatal units in level-2 + scoring. No neonatal unit achieved high scores of > 75%. DISCUSSION: Two scoring approaches reveal gaps in SSNC readiness with no neonatal units achieving high scores (> 75%). Government-led quality improvement teams can use these summary scores to identify areas for health systems change. Future analyses could determine which items are most directly linked with quality SSNC and newborn outcomes.

Development and Implementation of Digital Diagnostic Algorithms for Neonatal Units in Zimbabwe and Malawi: Development and Usability Study.

BACKGROUND: Despite an increase in hospital-based deliveries, neonatal mortality remains high in low-resource settings. Due to limited laboratory diagnostics, there is significant reliance on clinical findings to inform diagnoses. Accurate, evidence-based identification and management of neonatal conditions could improve outcomes by standardizing care. This could be achieved through digital clinical decision support (CDS) tools. Neotree is a digital, quality improvement platform that incorporates CDS, aiming to improve neonatal care in low-resource health care facilities. Before this study, first-phase CDS development included developing and implementing neonatal resuscitation algorithms, creating initial versions of CDS to address a range of neonatal conditions, and a Delphi study to review key algorithms. OBJECTIVE: This second-phase study aims to codevelop and implement neonatal digital CDS algorithms in Malawi and Zimbabwe. METHODS: Overall, 11 diagnosis-specific web-based workshops with Zimbabwean, Malawian, and UK neonatal experts were conducted (August 2021 to April 2022) encompassing the following: (1) review of available evidence, (2) review of country-specific guidelines (Essential Medicines List and Standard Treatment Guidelinesfor Zimbabwe and Care of the Infant and Newborn, Malawi), and (3) identification of uncertainties within the literature for future studies. After agreement of clinical content, the algorithms were programmed into a test script, tested with the respective hospital's health care professionals (HCPs), and refined according to their feedback. Once finalized, the algorithms were programmed into the Neotree software and implemented at the tertiary-level implementation sites: Sally Mugabe Central Hospital in Zimbabwe and Kamuzu Central Hospital in Malawi, in December 2021 and May 2022, respectively. In Zimbabwe, usability was evaluated through 2 usability workshops and usability questionnaires: Post-Study System Usability Questionnaire (PSSUQ) and System Usability Scale (SUS). RESULTS: Overall, 11 evidence-based diagnostic and management algorithms were tailored to local resource availability. These refined algorithms were then integrated into Neotree. Where national management guidelines differed, country-specific guidelines were created. In total, 9 HCPs attended the usability workshops and completed the SUS, among whom 8 (89%) completed the PSSUQ. Both usability scores (SUS mean score 75.8 out of 100 [higher score is better]; PSSUQ overall score 2.28 out of 7 [lower score is better]) demonstrated high usability of the CDS function but highlighted issues around technical complexity, which continue to be addressed iteratively. CONCLUSIONS: This study describes the successful development and implementation of the only known neonatal CDS system, incorporated within a bedside data capture system with the ability to deliver up-to-date management guidelines, tailored to local resource availability. This study highlighted the importance of collaborative participatory design. Further implementation evaluation is planned to guide and inform the development of health system and program strategies to support newborn HCPs, with the ultimate goal of reducing preventable neonatal morbidity and mortality in low-resource settings.

Development and Pilot Implementation of Neotree, a Digital Quality Improvement Tool Designed to Improve Newborn Care and Survival in 3 Hospitals in Malawi and Zimbabwe: Cost Analysis Study.

Background: Two-thirds of the 2.4 million newborn deaths that occurred in 2020 within the first 28 days of life might have been avoided by implementing existing low-cost evidence-based interventions for all sick and small newborns. An open-source digital quality improvement tool (Neotree) combining data capture with education and clinical decision support is a promising solution for this implementation gap. Objective: We present results from a cost analysis of a pilot implementation of Neotree in 3 hospitals in Malawi and Zimbabwe. Methods: We combined activity-based costing and expenditure approaches to estimate the development and implementation cost of a Neotree pilot in 1 hospital in Malawi, Kamuzu Central Hospital (KCH), and 2 hospitals in Zimbabwe, Sally Mugabe Central Hospital (SMCH) and Chinhoyi Provincial Hospital (CPH). We estimated the costs from a provider perspective over 12 months. Data were collected through expenditure reports, monthly staff time-use surveys, and project staff interviews. Sensitivity and scenario analyses were conducted to assess the impact of uncertainties on the results or estimate potential costs at scale. A pilot time-motion survey was conducted at KCH and a comparable hospital where Neotree was not implemented. Results: Total cost of pilot implementation of Neotree at KCH, SMCH, and CPH was US $37,748, US $52,331, and US $41,764, respectively. Average monthly cost per admitted child was US $15, US $15, and US $58, respectively. Staff costs were the main cost component (average 73% of total costs, ranging from 63% to 79%). The results from the sensitivity analysis showed that uncertainty around the number of admissions had a significant impact on the costs in all hospitals. In Malawi, replacing monthly web hosting with a server also had a significant impact on the costs. Under routine (nonresearch) conditions and at scale, total costs are estimated to fall substantially, up to 76%, reducing cost per admitted child to as low as US $5 in KCH, US $4 in SMCH, and US $14 in CPH. Median time to admit a baby was 27 (IQR 20-40) minutes using Neotree (n=250) compared to 26 (IQR 21-30) minutes using paper-based systems (n=34), and the median time to discharge a baby was 9 (IQR 7-13) minutes for Neotree (n=246) compared to 3 (IQR 2-4) minutes for paper-based systems (n=50). Conclusions: Neotree is a time- and cost-efficient tool, comparable with the results from limited similar mHealth decision-support tools in low- and middle-income countries. Implementation costs of Neotree varied substantially between the hospitals, mainly due to hospital size. The implementation costs could be substantially reduced at scale due to economies of scale because of integration to the health systems and reductions in cost items such as staff and overhead. More studies assessing the impact and cost-effectiveness of large-scale mHealth decision-support tools are needed.

Protecting small and sick newborn care in the COVID-19 pandemic: multi-stakeholder qualitative data from four African countries with NEST360.

BACKGROUND: Health system shocks are increasing. The COVID-19 pandemic resulted in global disruptions to health systems, including maternal and newborn healthcare seeking and provision. Yet evidence on mitigation strategies to protect newborn service delivery is limited. We sought to understand what mitigation strategies were employed to protect small and sick newborn care (SSNC) across 65 facilities Kenya, Malawi, Nigeria and Tanzania, implementing with the NEST360 Alliance, and if any could be maintained post-pandemic. METHODS: We used qualitative methods (in-depth interviews n=132, focus group discussions n=15) with purposively sampled neonatal health systems actors in Kenya, Malawi, Nigeria and Tanzania. Data were collected from September 2021 - August 2022. Topic guides were co-developed with key stakeholders and used to gain a detailed understanding of approaches to protect SSNC during the COVID-19 pandemic. Questions explored policy development, collaboration and investments, organisation of care, human resources, and technology and device innovations. Interviews were conducted by experienced qualitative researchers and data were collected until saturation was reached. Interviews were digitally recorded and transcribed verbatim. A common coding framework was developed, and data were coded via NVivo and analysed using a thematic framework approach. FINDINGS: We identified two pathways via which SSNC was strengthened. The first pathway, COVID-19 specific responses with secondary benefit to SSNC included: rapid policy development and adaptation, new and collaborative funding partnerships, improved oxygen systems, strengthened infection prevention and control practices. The second pathway, health system mitigation strategies during the pandemic, included: enhanced information systems, human resource adaptations, service delivery innovations, e.g., telemedicine, community engagement and more emphasis on planned preventive maintenance of devices. Chronic system weaknesses were also identified that limited the sustainability and institutionalisation of actions to protect SSNC. CONCLUSION: Innovations to protect SSNC in response to the COVID-19 pandemic should be maintained to support resilience and high-quality routine SSNC delivery. In particular, allocation of resources to sustain high quality and resilient care practices and address remaining gaps for SSNC is critical.

Neonatal inpatient dataset for small and sick newborn care in low- and middle-income countries: systematic development and multi-country operationalisation with NEST360.

BACKGROUND: Every Newborn Action Plan (ENAP) coverage target 4 necessitates national scale-up of Level-2 Small and Sick Newborn Care (SSNC) (with Continuous Positive Airway Pressure (CPAP)) in 80% of districts by 2025. Routine neonatal inpatient data is important for improving quality of care, targeting equity gaps, and enabling data-driven decision-making at individual, district, and national-levels. Existing neonatal inpatient datasets vary in purpose, size, definitions, and collection processes. We describe the co-design and operationalisation of a core inpatient dataset for use to track outcomes and improve quality of care for small and sick newborns in high-mortality settings. METHODS: A three-step systematic framework was used to review, co-design, and operationalise this novel neonatal inpatient dataset in four countries (Malawi, Kenya, Tanzania, and Nigeria) implementing with the Newborn Essential Solutions and Technologies (NEST360) Alliance. Existing global and national datasets were identified, and variables were mapped according to categories. A priori considerations for variable inclusion were determined by clinicians and policymakers from the four African governments by facilitated group discussions. These included prioritising clinical care and newborn outcomes data, a parsimonious variable list, and electronic data entry. The tool was designed and refined by > 40 implementers and policymakers during a multi-stakeholder workshop and online interactions. RESULTS: Identified national and international datasets (n = 6) contained a median of 89 (IQR:61-154) variables, with many relating to research-specific initiatives. Maternal antenatal/intrapartum history was the largest variable category (21, 23.3%). The Neonatal Inpatient Dataset (NID) includes 60 core variables organised in six categories: (1) birth details/maternal history; (2) admission details/identifiers; (3) clinical complications/observations; (4) interventions/investigations; (5) discharge outcomes; and (6) diagnosis/cause-of-death. Categories were informed through the mapping process. The NID has been implemented at 69 neonatal units in four African countries and links to a facility-level quality improvement (QI) dashboard used in real-time by facility staff. CONCLUSION: The NEST360 NID is a novel, parsimonious tool for use in routine information systems to inform inpatient SSNC quality. Available on the NEST360/United Nations Children's Fund (UNICEF) Implementation Toolkit for SSNC, this adaptable tool enables facility and country-level comparisons to accelerate progress toward ENAP targets. Additional linked modules could include neonatal at-risk follow-up, retinopathy of prematurity, and Level-3 intensive care.

Blood culture versus antibiotic use for neonatal inpatients in 61 hospitals implementing with the NEST360 Alliance in Kenya, Malawi, Nigeria, and Tanzania: a cross-sectional study.

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.

Changes in moderately low birthweight infant feeding, care, and health outcomes before compared to during the COVID-19 pandemic in Malawi.

Background: The coronavirus disease 2019 (COVID-19) and the measures taken to minimise its spread have significantly impacted mother- and infant-related healthcare. We describe the changes in newborn feeding, lactation support, and growth outcomes before compared to during the COVID-19 pandemic among moderately low birthweight infants (LBW) (1.5 to <2.5kg) in Malawi. Methods: The data presented here are part of the Low Birthweight Infant Feeding Exploration (LIFE) study, a formative, multisite, mixed methods observational cohort study. In this analysis, we included infants born at two public hospitals in Lilongwe, Malawi between 18 October 2019 and 29 July 2020. We categorised births as "pre-COVID-19 period" (before 1 April 2020) and "during COVID-19 period" (on or after 2 April 2020) and used descriptive statistics and mixed effects models to examine differences in birth complications, lactation support, feeding, and growth outcomes between the two time periods. Results: We included 300 infants and their mothers (n = 273) in the analysis. Most infants (n = 240) were born during the pre-COVID-19 period; 60 were born during the pandemic period. The latter group had a lower prevalence of uncomplicated births (35.8%) compared to pre-pandemic period group (16.7%) (P = 0.004). Fewer mothers reported early initiation of breastfeeding in the pandemic period (27.2%) compared to the pre-pandemic period (14.6%) (P = 0.053), along with significantly less breastfeeding support, particularly in view of discussion of proper latching (44.9% during COVID-19 vs 72.7% pre-COVID-19; P < 0.001) and physical support with positioning (14.3% vs 45.5% pre-COVID-19 P < 0.001). At 10 weeks of age, the prevalence of stunting was 51.0% pre-COVID-19 vs 45.1% during COVID-19 (P = 0.46), the prevalence of underweight was 22.5% pre-COVID-19 vs 30.4% during COVID-19 (P = 0.27), and the prevalence of wasting was 0% pre-COVID-19 vs 2.5% during COVID-19 (P = 0.27). Conclusions: Our findings highlight the continued need to optimise early initiation of breastfeeding and lactation support for infants during COVID-19 and future pandemics. More studies are needed to evaluate the long-term outcomes of moderately LBW born during the COVID-19 pandemic (including growth outcomes) and determine the impact of restrictive measures on access to lactation support and promotion of early initiation of breastfeeding.

Mortality by Admission Diagnosis in Children 1-60 Months of Age Admitted to a Tertiary Care Government Hospital in Malawi.

Diagnosis-specific mortality is a measure of pediatric healthcare quality that has been incompletely studied in sub-Saharan African hospitals. Identifying the mortality rates of multiple conditions at the same hospital may allow leaders to better target areas for intervention. In this secondary analysis of routinely collected data, we investigated hospital mortality by admission diagnosis in children aged 1-60 months admitted to a tertiary care government referral hospital in Malawi between October 2017 and June 2020. The mortality rate by diagnosis was calculated as the number of deaths among children admitted with a diagnosis divided by the number of children admitted with the same diagnosis. There were 24,452 admitted children eligible for analysis. Discharge disposition was recorded in 94.2% of patients, and 4.0% (N = 977) died in the hospital. The most frequent diagnoses among admissions and deaths were pneumonia/bronchiolitis, malaria, and sepsis. The highest mortality rates by diagnosis were found in surgical conditions (16.1%; 95% CI: 12.0-20.3), malnutrition (15.8%; 95% CI: 13.6-18.0), and congenital heart disease (14.5%; 95% CI: 9.9-19.2). Diagnoses with the highest mortality rates were alike in their need for significant human and material resources for medical care. Improving mortality in this population will require sustained capacity building in conjunction with targeted quality improvement initiatives against both common and deadly diseases.

Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree.

Introduction: Improving peri- and postnatal facility-based care in low-resource settings (LRS) could save over 6000 babies' lives per day. Most of the annual 2.4 million neonatal deaths and 2 million stillbirths occur in healthcare facilities in LRS and are preventable through the implementation of cost-effective, simple, evidence-based interventions. However, their implementation is challenging in healthcare systems where one in four babies admitted to neonatal units die. In high-resource settings healthcare systems strengthening is increasingly delivered via learning healthcare systems to optimise care quality, but this approach is rare in LRS. Methods: Since 2014 we have worked in Bangladesh, Malawi, Zimbabwe, and the UK to co-develop and pilot the Neotree system: an android application with accompanying data visualisation, linkage, and export. Its low-cost hardware and state-of-the-art software are used to support healthcare professionals to improve postnatal care at the bedside and to provide insights into population health trends. Here we summarise the formative conceptualisation, development, and preliminary implementation experience of the Neotree. Results: Data thus far from ~18 000 babies, 400 healthcare professionals in four hospitals (two in Zimbabwe, two in Malawi) show high acceptability, feasibility, usability, and improvements in healthcare professionals' ability to deliver newborn care. The data also highlight gaps in knowledge in newborn care and quality improvement. Implementation has been resilient and informative during external crises, for example, coronavirus disease 2019 (COVID-19) pandemic. We have demonstrated evidence of improvements in clinical care and use of data for Quality Improvement (QI) projects. Conclusion: Human-centred digital development of a QI system for newborn care has demonstrated the potential of a sustainable learning healthcare system to improve newborn care and outcomes in LRS. Pilot implementation evaluation is ongoing in three of the four aforementioned hospitals (two in Zimbabwe and one in Malawi) and a larger scale clinical cost effectiveness trial is planned.

Point-of-care ultrasound needs assessment in a paediatric acute care setting in Malawi.

OBJECTIVE: To describe the use of point-of-care ultrasound (POCUS) in an acute-care paediatric setting in Malawi, including clinical indications, types of examinations and frequency of positive findings. METHODS: Retrospective, cross-sectional study of a convenience sample of POCUS examinations performed in one tertiary referral hospital in Lilongwe, Malawi over 1 year. POCUS examinations were performed by Paediatric Emergency Medicine physician consultants as part of routine clinical practice and at the request of local clinicians. Images were saved along with the clinical indication and physician interpretation for quality review. Ultrasounds performed by the radiology department and those examinations that were technically faulty, missing clinical application or interpretation were excluded. RESULTS: In total, 225 ultrasounds of 142 patients were analysed. The most common clinical indications for which examinations were completed were respiratory distress (23%), oedema (11.7%) and shock/arrest (6.2%). The most common examinations performed were cardiac (41.8%) and lung (15.1%), focused assessment with sonography in trauma (FAST; 12.9%) and ultrasound-guided procedural examinations (9.8%). Pathology was identified in 68% of non-procedural examinations. Cardiac examinations demonstrated significant pathology, including reduced cardiac function (12.8%), gross cardiac structural abnormality (11.8%) and pericardial effusion (10.3%). CONCLUSIONS: POCUS was used for both clinical decision-making and procedural guidance, and a significant number of POCUS examinations yielded positive findings. Thus, we propose that cardiopulmonary, FAST and procedural examinations should be considered in future for the POCUS curriculum in this setting.

Protocol for an intervention development and pilot implementation evaluation study of an e-health solution to improve newborn care quality and survival in two low-resource settings, Malawi and Zimbabwe: Neotree.

INTRODUCTION: Every year 2.4 million deaths occur worldwide in babies younger than 28 days. Approximately 70% of these deaths occur in low-resource settings because of failure to implement evidence-based interventions. Digital health technologies may offer an implementation solution. Since 2014, we have worked in Bangladesh, Malawi, Zimbabwe and the UK to develop and pilot Neotree: an android app with accompanying data visualisation, linkage and export. Its low-cost hardware and state-of-the-art software are used to improve bedside postnatal care and to provide insights into population health trends, to impact wider policy and practice. METHODS AND ANALYSIS: This is a mixed methods (1) intervention codevelopment and optimisation and (2) pilot implementation evaluation (including economic evaluation) study. Neotree will be implemented in two hospitals in Zimbabwe, and one in Malawi. Over the 2-year study period clinical and demographic newborn data will be collected via Neotree, in addition to behavioural science informed qualitative and quantitative implementation evaluation and measures of cost, newborn care quality and usability. Neotree clinical decision support algorithms will be optimised according to best available evidence and clinical validation studies. ETHICS AND DISSEMINATION: This is a Wellcome Trust funded project (215742_Z_19_Z). Research ethics approvals have been obtained: Malawi College of Medicine Research and Ethics Committee (P.01/20/2909; P.02/19/2613); UCL (17123/001, 6681/001, 5019/004); Medical Research Council Zimbabwe (MRCZ/A/2570), BRTI and JREC institutional review boards (AP155/2020; JREC/327/19), Sally Mugabe Hospital Ethics Committee (071119/64; 250418/48). Results will be disseminated via academic publications and public and policy engagement activities. In this study, the care for an estimated 15 000 babies across three sites will be impacted. TRIAL REGISTRATION NUMBER: NCT0512707; Pre-results.

Evaluation of a Point-of-Care Test for Bilirubin in Malawi.

OBJECTIVES: BiliSpec is a low-cost spectrophotometric reader and disposable paper-based strip to quantify total serum bilirubin from several blood drops. This study was a prospective evaluation of BiliSpec in 2 neonatal wards in Malawi compared with a reference standard bilirubinometer over a large range of bilirubin and hematocrit levels. METHODS: The accuracy of BiliSpec and a transcutaneous bilirubinometer were compared with the reference standard of spectrophotometry for 475 blood samples collected from 375 subjects across a range of total serum bilirubin concentrations from 0.0 to 33.7 mg/dL. The development of error grids to assess the clinical effects of measurement differences is reported. RESULTS: BiliSpec was found to have a mean bias of -0.48 mg/dL and 95% limits of agreement of -5.09 mg/dL to +4.12 mg/dL. Results show 90.7% of BiliSpec measurements would have resulted in the same clinical decision as the reference standard, whereas 55.0% of transcutaneous bilirubin measurements would have resulted in the same clinical decision as the reference standard. CONCLUSIONS: This evaluation supports use of BiliSpec to provide accurate, low-cost, point-of-care bilirubin measurements in low-resource hospitals. Future work is needed to evaluate BiliSpec among a larger number of users.

Indirect impacts of the COVID-19 pandemic at two tertiary neonatal units in Zimbabwe and Malawi: an interrupted time series analysis.

OBJECTIVES: To examine indirect impacts of the COVID-19 pandemic on neonatal care in low-income and middle-income countries. DESIGN: Interrupted time series analysis. SETTING: Two tertiary neonatal units in Harare, Zimbabwe and Lilongwe, Malawi. PARTICIPANTS: We included a total of 6800 neonates who were admitted to either neonatal unit from 1 June 2019 to 25 September 2020 (Zimbabwe: 3450; Malawi: 3350). We applied no specific exclusion criteria. INTERVENTIONS: The first cases of COVID-19 in each country (Zimbabwe: 20 March 2020; Malawi: 3 April 2020). PRIMARY OUTCOME MEASURES: Changes in the number of admissions, gestational age and birth weight, source of admission referrals, prevalence of neonatal encephalopathy, and overall mortality before and after the first cases of COVID-19. RESULTS: Admission numbers in Zimbabwe did not initially change after the first case of COVID-19 but fell by 48% during a nurses' strike (relative risk (RR) 0.52, 95% CI 0.41 to 0.66, p<0.001). In Malawi, admissions dropped by 42% soon after the first case of COVID-19 (RR 0.58, 95% CI 0.48 to 0.70, p<0.001). In Malawi, gestational age and birth weight decreased slightly by around 1 week (beta -1.4, 95% CI -1.62 to -0.65, p<0.001) and 300 g (beta -299.9, 95% CI -412.3 to -187.5, p<0.001) and outside referrals dropped by 28% (RR 0.72, 95% CI 0.61 to 0.85, p<0.001). No changes in these outcomes were found in Zimbabwe and no significant changes in the prevalence of neonatal encephalopathy or mortality were found at either site (p>0.05). CONCLUSIONS: The indirect impacts of COVID-19 are context-specific. While our study provides vital evidence to inform health providers and policy-makers, national data are required to ascertain the true impacts of the pandemic on newborn health.

Usability-Focused Development and Usage of NeoTree-Beta, an App for Newborn Care in a Low-Resource Neonatal Unit, Malawi.

Background: Neonatal mortality is high in low-resource settings. NeoTree is a digital intervention for neonatal healthcare professionals (HCPs) aiming to achieve data-driven quality improvement and improved neonatal survival in low-resource hospitals. Optimising usability with end-users could help digital health interventions succeed beyond pilot stages in low-resource settings. Usability is the quality of a user's experience when interacting with an intervention, encompassing their effectiveness, efficiency, and overall satisfaction. Objective: To evaluate the usability and usage of NeoTree beta-app and conduct Agile usability-focused intervention development. Method: A real-world pilot of NeoTree beta-app was conducted over 6 months at Kamuzu Central Hospital neonatal unit, Malawi. Prior to deployment, think-aloud interviews were conducted to guide nurses through the app whilst voicing their thoughts aloud (n = 6). System Usability Scale (SUS) scores were collected before the implementation of NeoTree into usual clinical care and 6 months after implementation (n = 8 and 8). During the pilot, real-world user-feedback and user-data were gathered. Feedback notes were subjected to thematic analysis within an Agile "product backlog." For usage, number of users, user-cadre, proportion of admissions/outcomes recorded digitally, and median app-completion times were calculated. Results: Twelve overarching usability themes generated 57 app adjustments, 39 (68%) from think aloud analysis and 18 (32%) from the real-world testing. A total of 21 usability themes/issues with corresponding app features were produced and added to the app. Six themes relating to data collection included exhaustiveness of data schema, prevention of errors, ease of progression, efficiency of data entry using shortcuts, navigation of user interface (UI), and relevancy of content. Six themes relating to the clinical care included cohesion with ward process, embedded education, locally coherent language, adaptability of user-interface to available resources, and printout design to facilitate handover. SUS scores were above average (88.1 and 89.4 at 1 and 6 months, respectively). Ninety-three different HCPs of 5 cadres, recorded 1,323 admissions and 1,197 outcomes over 6 months. NeoTree achieved 100% digital coverage of sick neonates admitted. Median completion times were 16 and 8 min for admissions and outcomes, respectively. Conclusions: This study demonstrates optimisation of a digital health app in a low-resource setting and could inform other similar usability studies apps in similar settings.

Infection prevention and care bundles addressing health care-associated infections in neonatal care in low-middle income countries: a scoping review.

BACKGROUND: Health care-associated infections (HCAI) in neonatal units in low- and middle-income countries (LMIC) are a major cause of mortality. This scoping review aimed to synthesise published literature on infection prevention and care bundles addressing neonatal HCAI in LMICs and to construct a Classification Framework for their components (elements). METHODS: Five electronic databases were searched between January 2001 and July 2020. A mixed-methods approach was applied: qualitative content analysis was used to build a classification framework to categorise bundle elements and the contents of the classification groups were then described quantitatively. FINDINGS: 3619 records were screened, with 44 eligible studies identified. The bundle element Classification Framework created involved: (1) Primary prevention, (2) Detection, (3) Case management, and Implementation (3 + I). The 44 studies included 56 care bundles with 295 elements that were then classified. Primary prevention elements (128, 43%) predominated of which 71 (55%) focused on central line catheters and mechanical ventilators. Only 12 elements (4%) were related to detection. A further 75 (25%) elements addressed case management and 66 (88%) of these aimed at outbreak control. INTERPRETATION: The 3 + I Classification Framework was a feasible approach to reporting and synthesising research for infection-relevant bundled interventions in neonatal units. A shift towards the use in infection prevention and care bundles of primary prevention elements focused on the neonate and on commonly used hospital devices in LMIC (e.g., self-inflating bags, suctioning equipment) would be valuable to reduce HCAI transmission. Detection elements were a major gap. FUNDING: This work was made possible in part by the John D. and Catherine T. MacArthur Foundation, the Bill & Melinda Gates Foundation, ELMA Philanthropies, The Children's Investment Fund Foundation UK, The Lemelson Foundation, and the Ting Tsung and Wei Fong Chao Foundation under agreements to William Marsh Rice University. The project leading to these results has also received the support of a fellowship from the "la Caixa" Foundation (ID 100010434). The fellowship code is LCF/BQ/EU19/11710040. EJAF is an Academic Clinical Fellow whose salary is funded by the UK National Institute for Health Research (NIHR). NES receives a Research Training Program Scholarship (Australian Commonwealth Government).

Palliative Care Services within a Pediatric Hematology-Oncology Program in a Low-Resource Setting.

CONTEXT: Outcomes for children with cancer in sub-Saharan Africa (SAA) are dismal due to delayed diagnosis and limited access to curative therapy. When establishing a pediatric hematology-oncology (PHO) program in low-resource settings, early integration of palliative care services becomes essential. While palliative care is a human right, equitable distribution is lacking. OBJECTIVES: We aim to describe our experience establishing a palliative care program, the services offered, and the distribution of patients served. METHODS: This is a brief description of our PHO palliative care program in Lilongwe, Malawi at a tertiary care center and a three-year retrospective review of activities (2017-2020). Services offered include inpatient, outpatient, home visits, end of life care, and strengthening of referral systems. RESULTS: Over the three-year period, 315 patients were enrolled. 57% (n=179) were male. The median age was seven years (5 months-22 years). Patients served were from 17 of 28 districts within Malawi. Diagnoses of patients included 43% solid tumors (n=135), 22% lymphoma (n=68), 15% leukemia (n=47), and 21% hematologic disease (n=65). 40% of patients have died (n=125), with 53% of deaths occurring at home (n=66), 22% in the hospital (n=28), and 25% at unknown locations (n=31). CONCLUSION: Palliative care is a critical component of PHO programs worldwide. Programs must leverage existing networks to ensure optimal care to children and families. We demonstrate the feasibility of integrating palliative care services within a PHO program in a low-resource setting, which could serve as a model for other countries in SSA.

Software development process of Neotree - a data capture and decision support system to improve newborn healthcare in low-resource settings.

The global priority of improving neonatal survival could be tackled through the universal implementation of cost-effective maternal and newborn health interventions. Despite 90% of neonatal deaths occurring in low-resource settings, very few evidence-based digital health interventions exist to assist healthcare professionals in clinical decision-making in these settings. To bridge this gap, Neotree was co-developed through an iterative, user-centered design approach in collaboration with healthcare professionals in the UK, Bangladesh, Malawi, and Zimbabwe. It addresses a broad range of neonatal clinical diagnoses and healthcare indicators as opposed to being limited to specific conditions and follows national and international guidelines for newborn care. This digital health intervention includes a mobile application (app) which is designed to be used by healthcare professionals at the bedside. The app enables real-time data capture and provides education in newborn care and clinical decision support via integrated clinical management algorithms. Comprehensive routine patient data are prospectively collected regarding each newborn, as well as maternal data and blood test results, which are used to inform clinical decision making at the bedside. Data dashboards provide healthcare professionals and hospital management a near real-time overview of patient statistics that can be used for healthcare quality improvement purposes. To enable this workflow, the Neotree web editor allows fine-grained customization of the mobile app. The data pipeline manages data flow from the app to secure databases and then to the dashboard. Implemented in three hospitals in two countries so far, Neotree has captured routine data and supported the care of over 21,000 babies and has been used by over 450 healthcare professionals. All code and documentation are open source, allowing adoption and adaptation by clinicians, researchers, and developers.

Blood transfusion and mortality in children with severe anaemia in a malaria-endemic region.

BACKGROUND: In children in sub-Saharan Africa, severe anaemia (SA) is an important cause of mortality, and malaria is a primary cause. The World Health Organization (WHO) recommends blood transfusion for all children with haemoglobin (Hb) <4 g/dL and for those with Hb 4-6 g/dL with signs of instability. In sub-Saharan Africa, evidence of the effect on mortality of transfusion in children with SA with and without malaria is mixed. AIM: To determine in children with and without malaria whether receipt of transfusion was associated with lower mortality at WHO transfusion thresholds. METHODS: This was a retrospective cohort study of 1761 children with SA (Hb ≤6 g/dL) admitted to Kamuzu Central Hospital in Malawi. In those whose Hb was 4-6 g/dL, mortality was compared by transfusion, stratified by haemoglobin, malaria status and signs of instability. RESULTS: Children with profound anaemia (Hb <4 g/dL) and malaria were the only subgroup who had a significant decrease in the odds of in-hospital death if they received a transfusion (OR 0.43, p = 0.01). Although children with Hb 4-6 g/dL and at least one sign of instability had higher mortality than children with none, there was no difference in the odds of mortality between those who received a transfusion and those who did not (OR 1.16, p = 0.62). CONCLUSIONS: This study suggests that transfusion of children with profound anaemia and malaria may confer increased in-hospital survival. An understanding of the factors associated with mortality from SA will allow for interventions to prioritise the provision of limited blood.