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Low levels of neonatal health services utilization and high neonatal deaths are often concentrated among socially and economically disadvantaged groups, especially in low-income countries. Therefore the aim of this study was to assess inequity in the use of neonatal health services in Southwest Ethiopia. A community-based cross-sectional study was conducted in 8 districts located in Jimma Zone, Southwest Ethiopia from 19 March to 28 April 2018. A total of 835 mothers were included in the study with systematic random sampling. Principal component analysis was conducted to develop wealth quintiles of the households. Equity in neonatal health services was measured using rate-ratio, concentration curve, concentration index, and analyzed by binary logistic regression. Neonates from richer families were 1.25 times more likely to use neonatal health services than the poorer households with a concentration index value of 0.07. Neonates from highly educated mothers have better used the services and the corresponding concentration index value of 0.03. Neonatal service utilization was 1.32 times higher in the highest wealth quintile in rural settings. Similarly, services delivered at health posts and hospitals were used 2.4 and 2 times more by the wealthy, whereas services given at health centers are more utilized by the poorest. Outputs of binary logistic regression analysis indicated that neonates from middle quintile wealth households were found to be better neonatal health service users [AOR_1.72, 95% CI: 1.04, 2.82]. Neonate born from a secondary school attended mother [AOR_3.56, 95% CI: 1.90, 6.69] were more likely to use neonatal health services. Neonatal health service utilization in Southwest Ethiopia is more common among neonates from richer households and more educated mothers. There is a big difference among the wealthy and poorer in a rural setting and among those who used health posts. Working on the social-determinants of health will facilitate eliminating inequity.

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OBJECTIVE: To analyse the trend change and level change of neonatal health services and neonatal mortality before and after the introduction of the Basic Public Health Service (BPHS) project in 2009. DESIGN AND SETTING: A national longitudinal study on neonatal mortality from 1991 to 2017 and neonatal health services from 2000 to 2017 was conducted based on data extracted from the National Neonatal Mortality Surveillance System and National Health Statistic Yearbook. The segmented linear regression model was used to assess the level changes and trend changes of the outcome variables before and after the introduction of BPHS project. Pearson correlation analysis as conducted to measure association between neonatal mortality rates (NMRs) and maternal health management rates (MMRs), neonatal visit rates, respectively. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome variables were national NMR, the gap of NMR between urban and rural areas, maternal health management rate and neonatal visit rate. RESULTS: The annual trend change coefficient of national NMR and the gap of NMR between urban and rural areas were -0.57 (p<0.01) and -0.49 (p<0.01) after the introduction of BPHS project, while the annual trend coefficient of the MMR and the neonatal visit rate were 1.21 (p<0.01) and 0.85 (p<0.01), respectively. The negative correlations were found between NMR and MMR (r=-0.79, p<0.01) and neonatal visit rate (r=-0.76, p<0.01). CONCLUSION: The BPHS project was found to be associated with increased volume of neonatal health services and reduced NMR. The design and implementation of this project may provide references to other low-income and middle-income countries.

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BACKGROUND: Quality improvement (QI) methods are effective in improving healthcare delivery using sustainable, collaborative, and cost-effective approaches. Systems-integrated interventions offer promise in terms of producing sustainable impacts on service quality and coverage, but can also improve important data quality and information systems at scale. METHODS: This study assesses the preliminary impacts of a first phase, quasi-experimental, QI health systems intervention on maternal and neonatal health outcomes in four pilot districts in Ethiopia. The intervention identified, trained, and coached QI teams to develop and test change ideas to improve service delivery. We use an interrupted time-series approach to evaluate intervention effects over 32-months. Facility-level outcome indicators included: proportion of mothers receiving four antenatal care visits, skilled delivery, syphilis testing, early postnatal care, proportion of low birth weight infants, and measures of quality delivery of childbirth services. RESULTS: Following the QI health systems intervention, we found a significant increase in the rate of syphilis testing (ß = 2.41, 95% CI = 0.09,4.73). There were also large positive impacts on health worker adherence to safe child birth practices just after birth (ß = 8.22, 95% CI = 5.15, 11.29). However, there were limited detectable impacts on other facility-usage indicators. Findings indicate early promise of systems-integrated QI on the delivery of maternal health services, and increased some service coverage. CONCLUSIONS: This study preliminarily demonstrates the feasibility of complex, low-cost, health-worker driven improvement interventions that can be adapted in similar settings around the world, though extended follow up time may be required to detect impacts on service coverage. Policy makers and health system workers should carefully consider what these findings mean for scaling QI approaches in Ethiopia and other similar settings.

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BACKGROUND: Disparity in resource allocation is an issue among various health delivery units in Ethiopia. To sufficiently address this problem decision-makers require evidence on efficient allocation of resources. Therefore, the purpose of this study was to assess the technical efficiency of primary health care units providing neonatal health services in Southwest Ethiopia. METHODS: Two-stage data envelopment analysis was conducted based on one-year (2016/17) data from 68 health posts and 23 health centers in Southwest Ethiopia. Primary data were collected from each of the facility, respective district health offices and finance and economic cooperation offices. Technical efficiency scores were calculated using data envelopment analysis software version 2.1. Tobit regression was then applied to identify determinants of technical efficiency. STATA version 14 was used in the regression model and for descriptive statistics. RESULTS: By utilizing the best combination of inputs, eight health posts (11.76%) and eight health centers (34.78%) were found to be technically efficient in delivering neonatal health services. Compared with others included in the analysis, inefficient health delivery units were using more human and non-salary recurrent resources. The regression model indicated that there was a positive association between efficiency and the health center head's years of experience and the facility's catchment population. Waiting time at the health posts was found to negatively affect efficiency. CONCLUSIONS: Most of health posts and the majority of health centers were found to be technically inefficient in delivering neonatal health services. This indicates issues with the performance of these facilities with regards to the utilization of inputs to produce the current outputs. The existing resources could be used to serve additional neonates in the facilities.