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Statistical Analysis of Health Insurance and Cash and Carry Systems in Cape Coast Teaching Hospital of Ghana

机译:加纳角海岸教学医院健康保险和现金及携带系统的统计分析

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The passage of National Health Insurance Scheme to replace the old system (called cash and carry) in Ghana seems to have raised many questions as to whether it has increased the rate at which people attend hospital and abolished cash and carry system. The data collected were hospital attendance for both health insurance and cash and carry system on monthly basis across age groups and gender for 2008-2017, obtained from Cape Coast Teaching Hospital. Chi-Square tests and the Box-Jenkins's methodology of time series analysis were employed to analyse the data. From the findings, the autocorrelation function (ACF) and partial autocorrelation function (PACF) plot suggested an AR process with order 1. Candidate models were obtained using the minimum AIC criteria to select adequate models and appropriate models were obtained as SARIMA (1,0,0) (0,1,0)_(12) model for insured (NHIS) and SARIMA (1,1,1) (2,0,1)_(12) model for uninsured (Cash and Carry system). Model diagnostics tests were performed using Ljung-Box test. The Chi-square tests inferred dependence in hospital attendance between insured and non-insured patients on gender and the years, In conclusion, insured patients will be increasing throughout the age groups and non-insured patients will be increasing for specific age groups 0-28 days to 15-17 years for the next 24 months. This research recommended among others that education should be given to the general public about the importance of health insurance, it registration and operations especially age group 0-28days to 15-17 years because they seem to continue the use of Cash and Carry System in seeking healthcare regardless of the introduction of NHIS.
机译:国民健康保险计划的通过,以取代加纳的旧系统(现钞和现钞系统),似乎引起了许多疑问,即它是否提高了人们住院的比率并废除了现钞和现钞系统。收集的数据是从开普敦教学医院获得的2008-2017年各个年龄段和性别的月均医疗保险和现金及随身携带系统的出勤率。使用卡方检验和Box-Jenkins的时间序列分析方法来分析数据。从发现中,自相关函数(ACF)和部分自相关函数(PACF)的图建议采用1阶AR过程。使用最小AIC标准选择合适的模型获得候选模型,并获得合适的模型作为SARIMA(1,0 ,0)(0,1,0)_(12)模型用于被保险人(NHIS),SARIMA(1,1,1)(2,0,1)_(12)模型用于非保险人(现金和携带系统)。使用Ljung-Box测试执行模型诊断测试。卡方检验可推断出被保险人与非被保险人之间就诊时间和性别对年龄的依赖性。总之,在特定年龄段中,被保险人将在增加,而在特定年龄段,非被保险人将在增加0-28岁接下来的24个月中的15至17天。这项研究建议,除其他外,应该对公众进行有关健康保险重要性的教育,因为它似乎在继续寻求现钞和携带系统以寻求健康保险的重要性,尤其是0-28天至15-17岁年龄段的人群医疗保健,而不管引入NHIS。

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