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1.
PLoS One ; 16(1): e0245839, 2021.
Article in English | MEDLINE | ID: mdl-33503048

ABSTRACT

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.


Subject(s)
Community-Based Health Insurance/statistics & numerical data , Cost of Illness , Diabetes Mellitus/economics , Adolescent , Adult , Community-Based Health Insurance/standards , Diabetes Mellitus/epidemiology , Ethiopia , Female , Humans , Male , Middle Aged
2.
Article in English | MEDLINE | ID: mdl-33218111

ABSTRACT

Ethiopia's Community-Based Health Insurance (CBHI) scheme was established with the objectives of enhancing access to health care, reducing out-of-pocket expenditure (OOP), mobilizing financial resources and enhancing the quality of health care. Previous analyses have shown that the scheme has enhanced health care access and led to reductions in OOP. This paper examines the impact of the scheme on health facility revenues and quality of care. This paper relies on a difference-in-differences approach applied to both panel and cross-section data. We find that CBHI-affiliated facilities experience a 111% increase in annual outpatient visits and annual revenues increase by 47%. Increased revenues are used to ameliorate drug shortages. These increases have translated into enhanced patient satisfaction. Patient satisfaction increased by 11 percentage points. Despite the increase in patient volume, there is no discernible increase in waiting time to see medical professionals. These results and the relatively high levels of CBHI enrollment suggest that the Ethiopian CBHI has been able to successfully negotiate the main stumbling block-that is, the poor quality of care-which has plagued similar CBHI schemes in Sub-Saharan Africa.


Subject(s)
Community-Based Health Insurance , Quality of Health Care , Community-Based Health Insurance/economics , Community-Based Health Insurance/standards , Ethiopia , Female , Health Expenditures/statistics & numerical data , Health Services Accessibility/statistics & numerical data , Humans , Male , Patient Satisfaction , Quality of Health Care/statistics & numerical data
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