Kenya's Grand Coalition Government was formed in the aftermath of a serious post-electoral crisis including widespread violence. No political progress has been recorded; in striking contrast to all expectations for more moderation and consensual preparation of a constitutional reform. Based on secondary data from textbooks, newspapers, journals, and documents from both governmental and non-governmental organisations, the author finds that the continuing wrangles within the Grand Coalition Government, the fear of the debilitating effects of a constitutional referendum and the hard-line positions on the contentious issues pose a big threat to the achievement of a new constitution before the 2012 Elections.
Access to public healthcare in Nairobi County is unequal among social classes. Lower social classes have worse healthcare than either the upper or the middle classes. These health inequalities are correlated with socioeconomic inequalities. The higher socioeconomic classes have better access to healthcare than the lower socioeconomic classes. Higher incomes, education, employment and wealth result in better health of the households in the County. Unequal access to healthcare contributes to disparities in health status, increases costs for both the insured and the uninsured. Lack of access to healthcare reduces disposable incomes, particularly burdening the lower income households. These households cannot afford the care they need. This has forced them to forego such care altogether. The objectives of the study were three, namely: to evaluate the influence of demographic variables in access to public healthcare, to evaluate the influence of socio-cultural factors in access to public health care, and to evaluate the influence of institutional factors in access to public healthcare. The study used descriptive design, specifically, cross-sectional design for collection, measurements and analysis of data. The study took place in Nairobi County. The target population was households living in Nairobi County, where the sample was drawn from. The sampling techniques included multi-stage random sampling, random sampling, stratifies random sampling, cluster random sampling, convenient sampling and purposive sampling. The sample size was obtained using Chadha's formula (2006) to arrive at 1066 sample size. Data collection instruments included observations, face-to-face interviews, questionnaires, in-depth interviews and focus group discussions. Qualitative data was analyzed thematically but quantitative data was analyzed using descriptive statistics. Data was analyzed using SPSS version 23. The results show that there were positive correlations between independent and dependent variables. The P-value was statistically significant.
Access to public healthcare in Nairobi County is unequal among social classes. Lower social classes have worse healthcare than either the upper or the middle classes. These health inequalities are correlated with socio-economic inequalities. The higher socio-economic classes have better access to healthcare than the lower socio-economic classes. Higher incomes, education, employment and wealth result in better health of the households in the County. Unequal access to healthcare contributes to disparities in health status, increases costs for both the insured and the uninsured. Lack of access to healthcare reduces disposable incomes, particularly burdening the lower income households. These households cannot afford the care they need. This has forced them to forego such care altogether. The objectives of the study were three, namely: to evaluate the influence of demographic variables in access to public healthcare, to evaluate the influence of socio-cultural factors in access to public health care, and to evaluate the influence of institutional factors in access to public healthcare. The study used descriptive design, specifically, cross-sectional design for collection, measurements and analysis of data. The study took place in Nairobi County. The target population was households living in Nairobi County, where the sample was drawn from. The sampling techniques included multi-stage random sampling, random sampling, stratifies random sampling, cluster random sampling, convenient sampling and purposive sampling. The sample size was obtained using Chadha's formula ( 2006) to arrive at 1066 sample size. Data collection instruments included observations, face-to-face interviews, questionnaires, in-depth interviews and focus group discussions. Qualitative data was analyzed thematically but quantitative data was analyzed using descriptive statistics. Data were analyzed using SPSS version 23. The results show that there were positive correlations between independent and dependent variables. The P-value was statistically significant. The results were not due to random chance and that P-0.01< 0.05 and this confirms a positive relations ships between the variables. The relationships were mutually inclusive and highly correlated. On that basis, the null hypotheses were rejected and the alternate hypotheses accepted. The results show that demographic (disposing of), socio-cultural (need) factors influence access to healthcare. Socioeconomic factors should be addressed to benefit all the households. Socio-cultural factors should be distributed fairly among the households. Health systems should be improved and adequately financed to provide the requisite resources to all the households.
This study examines the influence of institutional factors on access to public healthcare in Kenya, a case for Nairobi County. It addresses the influences of health policies, leadership and governance, health infrastructure, health facilities, health workers, health finances and health insurance. The objective of the study is to evaluate the influence of institutional variables in access of public healthcare. The study used data from a sample of 1066 households purposively selected from Nairobi County. All households were aged 15 years and above. The households were subjected to interviews that covered a wide range of topics. Descriptive design was chosen for the study. The study adopted multiple sampling methods for the study. These included purposive sampling, systematic sampling, snowball sampling and multi stage cluster sampling frame. The data was collected using various techniques or instruments which included observation, key informant interviews, questionnaires, in-depth interviews, and focus-group discussions. The data was processed using descriptive statistics. Correlation and regression analyses were used to correlate and interpret the data of the study. The findings show access to healthcare is inadequate and unevenly distributed among the households in Nairobi County. The factors attributed to these inequalities were inadequate and poorly implemented health policies, inadequate health facilities, and inadequate health workers, shortage of essential drugs, low level funding and poorly managed health insurance. This study argues that these institutional factors should be made adequate, accessible and quality improved. The focus should be on the lower social classes, who are deprived, and denied capabilities to access healthcare. This is despite the interventions made to access healthcare to the entire population in the County.
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