ObjectiveThe aim of the study was to measure technical and scale efficiency of public health centers in three districts of Jimma zone, Ethiopia. A two-stage data envelopment analysis was used. First, we estimated technical and scale efficiency of the health centers. In the second stage, institutional and environmental factors were against technical efficiency of the health centers to identify factors associated to efficiency of the health centers.ResultsEight out of the 16 health centers in the study were found to be technically efficient, with an average score of 90% (standard deviation = 17%). This indicates that on average they could have reduce their utilization of all inputs by about 10% without reducing output. On the other hand, 8 out of 16 health centers were found to be scale efficient, with an average scale efficiency score of 94% (standard deviation = 9%). The inefficient health centers had an average scale score of 89%; implying there is potential for increasing total outputs by about 11% using the existing capacity/size. Catchment population and number of clinical staff were found to be directly associated with efficiency, while the number of nonclinical staff was found to be inversely associated with efficiency.

BACKGROUND: Professional commitment is beyond a commitment for a particular organization and implies the individuals’ perspective towards their profession and the motivation that they have to stay in their job with willingness to strive and uphold the values and goals of the profession. InEthiopia, uptake of institutional delivery services is low. However, the level and factors associated with professional commitment is not known so far. Hence, our objective is to assess the level and factors associated with commitment of health professionals providing institutional delivery services in public health facilities of  Jimma Zone, Southwest Ethiopia.METHODS: A facility-based cross-sectional study design was conducted from March 01-20, 2016. A total of 442 eligible health professionals were included from randomly selected 7 districts and 47 respective health facilities. Health professionals were requested to fill self-administered questionnaire. After checking its completeness, the data was entered into EPI data version 3.1 and exported to SPSS version 20 for statistical analysis. Factor analysis was conducted. Simple and multiple linear regression were done using 95%CI and significance was declared at P<0.05. All assumptions of linear regression and principal component analysis were checked.RESULTS: The percentage mean score of professional commitment was 72.71% (SD21.88). The percentage mean score for perceived maternal health goal scale was 68.37% with the total variance explained being 69.68%. Perceived staff interaction, work-life balance, affective organizational commitment, normative organizational commitment, personal characteristics and perceived maternal health goal were independent predictors of professional commitment.CONCLUSION: The percentages mean score of professional commitment was medium. Hence, Health professionals should foster their level of professional commitment to increase uptake of institutional delivery services.KEYWORDS: Commitment, health professionals, Institutional delivery service uptake

Background Globally, diabetes mellitus exerts an economic burden on patients and their families. However, the economic burden of diabetes mellitus and its associated factors were not well studied in Ethiopia. Therefore, the aim of this study is to assess the economic burden of diabetes mellitus and its associated factors among diabetic patients in public hospitals of Bahir Dar city administration, Ethiopia. Methods Across sectional study was conducted on 422 diabetic patients. The patients were selected by simple random sampling method. The prevalence-based model was used to estimate the costs on patients’ perspective. Bottom up and human capital approaches were used to estimate the direct and indirect costs of the patients respectively. Wealth index was constructed using principal component analysis by SPSS. Forty percent of nonfood threshold level was used to measure catastrophic diabetic care expenditure of diabetic patients. Whereas, the World Bank poverty line (the $1.90-a-day poverty line) was used to measure impoverishment of patients due to expenses of diabetes mellitus care. Data were entered by Epi data version 3.1and exported to SPSS version 23 for analysis. Simple and multiple logistic regressions were used. Results Four hundred one respondents were interviewed with response rate of 95%. We found that 239 (59.6%) diabetic patients incurred catastrophic diabetic care expenditure at 40% nonfood threshold level. Whereas, 20 (5%) diabetic patients were impoverished by diabetic care spending at the $1.90-a-day poverty line. Educational status of respondent, educational status of the head of household, occupation and wealth status were statistically associated with the catastrophic diabetic care expenditure. Conclusions The study revealed that the economic burden of diabetic care is very disastrous among the less privileged populations: the less educated, the poorest and unemployed. Therefore, all concerned stakeholders should design ways that can reduce the financial hardship of diabetic care among diabetic patients.

BackgroundDisparity 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.MethodsTwo-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.ResultsBy 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.ConclusionsMost 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.

As the Ethiopian health system faced critical resource constraints, wise use of the available health resources is a priority agenda. Therefore, our study aimed to assess technical efficiency of maternal and reproductive health services in public hospitals of Oromia regional state, Ethiopia. Two-stage data envelopment analysis was performed among 14 hospitals with input orientation and variable returns to scale assumptions. Technical efficiency scores were computed at the first stage, and predictors were determined using Tobit regression at the second stage. The assessment revealed that 12 (85.7%) hospitals were pure technical efficient and 9 (64.29%) hospitals were scale efficient. Level (primary/general) (β = 1.17, 95% confidence interval [CI] = 0.16-2.18), service years (β = 0.02, 95% CI = 0.003-0.03), and size of catchment population (β = 5.58E–07, 95% CI = 2.95E–08 to 1.09E–06) were positively associated with technical efficiency of maternal and reproductive health service, whereas average waiting time for maternal health service (β = –0.03, 95% CI = –0.05 to −0.01) was negatively associated with efficiency. In conclusion, most of the hospitals were technically efficient and around two-thirds were operating scale efficient. Allocation of more resources to older secondary hospitals with larger catchment population could result in more efficient use of resources for maternal and reproductive health service delivery.