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BACKGROUND: In 2019, 2.4 million neonates died globally, with most deaths occurring in low-resource settings. Despite the introduction of neonatal intensive care units (NICUs) in these settings, neonatal mortality remains high, and caring for sick neonates around the clock can be challenging due to limited staff and resources. OBJECTIVE: To evaluate whether neonatal intensive care admissions during daytime and overnight hours affects in-hospital neonatal mortality. METHODS: A retrospective case-control study was conducted using 2016 chart data at a University hospital in Ethiopia. Cases were defined as neonates who died in the NICU, and controls were defined as neonates who survived. Overnight hours were defined as 17:00 to 07:59, and day hours were defined as 08:00 to 16:59. Univariate and multivariate logistic regressions were used to investigate the relationship between time of admission and mortality, along with perinatal characteristics. RESULTS: A total of 812 neonates, 207 cases and 605 controls, met inclusion criteria. There were 342 admissions during the day and 470 overnight. Neonatal mortality (aOR 1.02, 95% CI [0.64-1.62], p = 0.93) was not associated with overnight admissions after controlling for maternal age, parity, C-section, birthweight, and gestational age, respiratory distress, and admission level of consciousness. Admission heart rate >160 (aOR 0.52, 95% CI [0.30-0.91], p = 0.02) was the only variable significantly associated with overnight admissions. CONCLUSION: Being admitted overnight to the NICU in Gondar, Ethiopia was not associated with increased mortality, consistent with a constant level of care, regardless of the time of admission. Further qualitative and implementation research are needed to understand contextual factors that have affected these data.

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BACKGROUND: A compassionate, respectful, and caring (CRC) health professional is very important for human-centered care, serving clients ethically and with respect, adhering to the professional oath, and serving as a model for young professionals. As countries try to achieve universal health coverage (UHC), quality delivery of health services is crucial. CRC health care is an initiative around the need to provide quality care services to clients and patients. However, there is an evidence gap on the status of CRC health care service delivery. OBJECTIVE: This scoping review aimed to map global evidence on the status of CRC health service delivery practice. METHODS: An exhaustive literature review and Delphi technique were used to answer the 2 research questions: "What is the current status of CRC health care practices among health workers?" and "Is it possible for health professionals, health managers, administrators, and policy makers to incorporate it into their activity while designing strategies that could improve the humanistic and holistic approach to health care provision?" The studies were searched from the year 2014 to September 2020 using electronic databases such as MEDLINE (PubMed), Cochrane Library, Web of Science, Hinari, and the World Health Organization (WHO) library. Additionally, grey literature such as Google, Google Scholar, and WorldWideScience were scrutinized. Studies that applied any study design and data collection and analysis methods related to CRC care were included. Two authors extracted the data and compared the results. Discrepancies were resolved by discussion, or the third reviewer made the decision. Findings from the existing literature were presented using thematic analysis. RESULTS: A total of 1193 potentially relevant studies were generated from the initial search, and 20 studies were included in the final review. From this review, we identified 5 thematic areas: the status of CRC implementation, facilitators for CRC health care service delivery, barriers to CRC health care delivery, disrespectful and abusive care encountered by patients, and perspectives on CRC. The findings of this review indicated that improving the mechanisms for monitoring health facilities, improving accountability, and becoming aware of the consequences of maltreatment within facilities are critical steps to improving health care delivery practices. CONCLUSIONS: This scoping review identified that there is limited CRC service provision. Lack of training, patient flow volume, and bed shortages were found to be the main contributors of CRC health care delivery. Therefore, the health care system should consider the components of CRC in health care delivery during in-service training, pre-service training, monitoring and evaluation, community engagement, workload division, and performance appraisal.

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BACKGROUND: For evidence-based decision-making, there is a need for quality, timely, relevant and accessible information at each level of the health system. Limited use of local data at each level of the health system is reported to be a main challenge for evidence-based decision-making in low- and middle-income countries. Although evidence is available on the timeliness and quality of local data, we know little about how it is used for decision-making at different levels of the health system. Therefore, this study aimed to assess the level of data use and its effect on data quality and shared accountability at different levels of the health system. METHODS: An implementation science study was conducted using key informants and document reviews between January and September 2017. A total of 21 key informants were selected from community representatives, data producers, data users and decision-makers from the community to the regional level. Reviewed documents include facility reports, district reports, zonal reports and feedback in supervision from the district. Thematic content analysis was performed for the qualitative data. RESULTS: Respondents reported that routine data use for routine decision-making was low. All health facilities and health offices have a performance monitoring team, but these were not always functional. Awareness gaps, lack of motivating incentives, irregularity of supportive supervision, lack of community engagement in health report verification as well as poor technical capacity of health professionals were found to be the major barriers to data use. The study also revealed that there are no institutional or national-level regulations or policies on the accountability mechanisms related to health data. The community-level Health Development Army programme was found to be a strong community engagement approach that can be leveraged for data verification at the source of community data. CONCLUSION: The culture of using routine data for decision-making at the local level was found to be low. Strengthening the capacity of health workers and performance monitoring teams, introducing incentive mechanisms for data use, engaging the community in data verification and introducing accountability mechanisms for health data are essential to improve data use and quality.

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BACKGROUND: WHO does not recommend community-level health workers (CLHWs) using integrated community case management (iCCM) to treat 7-59 days old infants with fast breathing with oral amoxicillin, whereas World Health Organization (WHO) integrated management of childhood illness (IMCI) recommends it. We want to collect evidence to help harmonization of both protocols. METHODS: A cluster, randomized, open-label trial will be conducted in Africa and Asia (Ethiopia, Malawi, Bangladesh and India) using a common protocol with the same study design, inclusion criteria, intervention, comparison, and outcomes to contribute to the overall sample size. This trial will also identify hypoxaemia in young infants with fast breathing. CLHWs will assess infants for fast breathing, which will be confirmed by a study supervisor. Enrolled infants in the intervention clusters will be treated with oral amoxicillin, whereas in the control clusters they will be managed as per existing iCCM protocol. An independent outcome assessor will assess all enrolled infants on days 6 and 14 of enrolment for the study outcomes in both intervention and control clusters. Primary outcome will be clinical treatment failure by day 6. This trial will obtain approval from the WHO and site institutional ethics committees. CONCLUSIONS: If the research shows that CLHWs can effectively and safely treat fast breathing pneumonia in 7-59 days old young infants, it will increase access to pneumonia treatment substantially for infants living in communities with poor access to health facilities. Additionally, this evidence will contribute towards the review of the current iCCM protocol and its harmonization with IMCI protocol. TRIAL REGISTRATION: The trial is registered at AZNCTR International Trial Registry as ACTRN12617000857303.

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BACKGROUND: Early warning scores for neonatal mortality have not been designed for low income countries. We developed and validated a score to predict mortality upon admission to a NICU in Ethiopia. METHODS: We conducted a retrospective case-control study at the University of Gondar Hospital, Gondar, Ethiopia. Neonates hospitalized in the NICU between January 1, 2016 to June 31, 2017. Cases were neonates who died and controls were neonates who survived. RESULTS: Univariate logistic regression identified variables associated with mortality. The final model was developed with stepwise logistic regression. We created the Neonatal Mortality Score, which ranged from 0 to 52, from the model's coefficients. Bootstrap analysis internally validated the model. The discrimination and calibration were calculated. In the derivation dataset, there were 207 cases and 605 controls. Variables associated with mortality were admission level of consciousness, admission respiratory distress, gestational age, and birthweight. The AUC for neonatal mortality using these variables in aggregate was 0.88 (95% CI 0.85-0.91). The model achieved excellent discrimination (bias-corrected AUC) under internal validation. Using a cut-off of 12, the sensitivity and specificity of the Neonatal Mortality Score was 81 and 80%, respectively. The AUC for the Neonatal Mortality Score was 0.88 (95% CI 0.85-0.91), with similar bias-corrected AUC. In the validation dataset, there were 124 cases and 122 controls, the final model and the Neonatal Mortality Score had similar discrimination and calibration. CONCLUSIONS: We developed, internally validated, and externally validated a score that predicts neonatal mortality upon NICU admission with excellent discrimination and calibration.

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Health programs are reliant on complex decision-making to efficiently utilize limited resources, but local-level data use is still challenging. This study aimed to assess barriers to fostering local-level data use culture at each level of a health system. Results show that awareness gaps, lack of motivation, inconsistent supervision, poor community engagement, and lack of accountability are major bottlenecks. Establishing an accountability system and capacity building on health data use could improve its implementation.

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BACKGROUND: Anti-Retroviral Therapy (ART) care is a lifelong treatment, which needs accurate and reliable data collected for long period of time. Poor quality of medical records data remains a challenge and is directly related to the quality of care of patients. To improve this, there is an increasing trend to implement electronic medical record (EMR) in hospitals. However, there is little evidence on the impact of EMR on the quality of health data in low- resource setting hospitals like Ethiopia. This comparative study aims to fill this evidence gap by assessing the completeness and reliability of paper-based and electronic medical records and explore the challenges of ensuring data quality at the Anti-Retroviral Therapy (ART) clinic at the University of Gondar Referral Hospital in Northwest Ethiopia. METHODS: An institution-based comparative cross-sectional study, supplemented with a qualitative approach was conducted from February 1 to March 30, 2017 at the ART clinic of the University of Gondar Hospital. A total of 250 medical records having both electronic and paper-based versions were collected and assessed. A national ART registration form which consists of 40 ART data elements was used as a checklist to assess completeness and reliability dimensions of data quality on medical records of patients on HIV care. Kappa statistics were computed to describe the level of data agreement between paper-based and electronic records across patient characteristics. In-depth interviews were conducted using semi-structured questionnaires with ten key informants to explore the challenges related with the quality of medical records. Responses of the key informant interviews were analyzed using thematic analysis. RESULTS: The overall completeness of medical records was 78% with 95% CI (70.8% - 85.1%) in paper-based and 76% with 95%CI (67.8% - 83.2%) EMR. The data reliability measured in Kappa statistics shows strong agreements on the socio-demographic data such as educational status 0.93 (0.891, 0.963), WHO staging 0.86 (0.808, 0.906); general appearance 0.83 (0.755, 0.892) and patient referral record 0.87 (0.795, 0.932). The major challenges hindering good data quality was the current side by side dual data documentation practice (the need to document both on the paper and the EMR for a single record), patient overload and low data documentation practice of health workers. CONCLUSION: The overall completeness of ART medical records was still slightly better in paper-based records than EMR. The main reason affecting the EMR data quality was the current dual documentation practice both on the paper and electronic for each patient in the hospital and the high load of patients in the clinic. The hospital management need to decide to use either the paper or the electronic system and build the capacity of health workers to improve data quality in the hospital.

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BACKGROUND: Anterior fontanelle is the largest, prominent and most important fontanelle, which is used for clinical evaluation. It is mainly characterized by its size and shape variation and is possibly influenced by gender, race and genetics. Understanding the variation of anterior fontanelle is used for recognition of different medical disorders and abnormal skeletal morphogenesis. OBJECTIVE: To determine the mean size of anterior fontanelle among term neonates on the first day of life born at University of Gondar Hospital, Gondar Town, Northwest Ethiopia, 2018. METHODS: Descriptive cross sectional study design was undertaken in 384 term and apparently healthy neonates, using standard methods. Descriptive analysis, student t-test, one way ANOVA and Pearson correlation coefficient were implemented. RESULTS: In this study, the mean size of anterior fontanelle in term neonates was 3.00 ± 0.62 cm (range 1.70-5.50 cm). The mean size of anterior fontanelle was 3.10 ± 0.66 cm for males, and 2.88 ± 0.57 cm for females. There was statistically significant difference in anterior fontanelle size in neonates of different genders (p<0.001), mode of delivery (p<0.001) and duration of labour (p = 0.006). However, the size of anterior fontanelle was not significantly affected by the birth order, onset of labour and socio-demographic variables of the mother except occupation of the mother (p = 0.01). There was a significant positive correlation between the mean size of anterior fontanelle with birth weight (r = 0.11; p = 0.04) and head circumference (r = 0.17; p = 0.001). CONCLUSIONS: At term, male neonates had significantly larger anterior fontanelle than female neonates and anterior fontanelle size has a direct relationship with birth weight and head circumference.

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BACKGROUND: Immunisation remains one of the most important and cost-effective interventions to reduce vaccine-preventable child morbidity, disability and mortality. Health programmes like the Expanded Program of Immunization rely on complex decision-making and strong local level evidence is important to effectively and efficiently utilise limited resources. Lack of data use for decision-making at each level of the health system remains the main challenge in most developing countries. While there is much evidence on data quality and how to improve it, there is a lack of sufficient evidence on why the use of data for decision-making at each level of the health system is low. Herein, we describe a comprehensive implementation science study that will be conducted to identify organisational, technical and individual level factors affecting local data use at each level of the Ethiopian health system. METHODS: We will apply a mixed methods approach using key informant interviews and document reviews. The qualitative data will be gathered through key informant interviews using a semi-structured guide with open- and closed-ended questions with four categories of respondents, namely decision-makers, data producers, data users and community representatives at the federal, regional, zonal, woreda and community levels of the health system. The document review will be conducted on selected reports and feedback documented at different levels of the health system. Data will be collected from July 2017 to March 2018. Descriptive statistics will be analysed for the quantitative study using SPSS version 20 software and thematic content analysis will be performed for the qualitative part using NVivo software. DISCUSSION: Appropriate and timely use of health and health-related information for decision-making is an essential element in the process of transforming the health sector. The findings of the study will inform stakeholders at different levels on the institutionalisation of evidence-based practice in immunisation programmes.

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