Browsing by Author "Nyamai, Joseph Juma"

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    PublicationOpen Access
    Determinants of data-driven decision-making among health providers: a case of Mombasa county, Kenya
    (International Journal of Community Medicine and Public Health, 2024-05) Muhula, Sally Wangige; Nyamai, Joseph Juma; Odongo, Alfred Owino; Kariuki, Peterson
    Background:Healthcare professionals understand how important it is to turn health data into information for informed decision-making. However, a lack of trustworthy and up-to-date health information is caused by inadequate investment in infrastructure for data collection, analysis, dissemination, and use. The aim of the study was to determine data-driven decision-making among health providers, acase of Mombasa County, Kenya.Methods:The study employed an analytical cross-sectional study design where a stratified random sampling approach was utilized to recruit respondents into the study. The Yamane formula of sample size calculation was used to recruit 168 study partakers for this study.Results:The outcomes indicated that quality data-driven decision-making exhibited a substantial correlation withtechnical factors (r=0.642, p value=0.000). Furthermore, the findings highlighted a significant correlation between quality data-driven decision-making and behavioral factors (r=0.821, p value=0.000). Additionally, the study's results revealed a marked correlation between quality data-propelled decision-making alongside organizational factors (r=0.819, p value=0.000).Conclusions:The likelihood ratio tests demonstrated that both technical and organizational factors significantly predicted data-driven decision-making among health providers, whereas behavioral factors did not have a statistically significant impact. There is a need to provide training for health workers at the county level to enhance data utilization skills, ensure thorough data verification before submission, and promote the use of health information in decision-making.
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    PublicationOpen Access
    Determinants of data-driven decision-making among health providers: a case of Mombasa county, Kenya
    (International Journal of Community Medicine and Public Health, 2024-05-30) Muhula, Sally Wangige; Nyamai, Joseph Juma; Odongo, Alfred Owino; Kariuki, Peterson
    Background:Healthcare professionals understand how important it is to turn health data into information for informed decision-making. However, a lack of trustworthy and up-to-date health information is caused by inadequate investment in infrastructure for data collection, analysis, dissemination, and use. The aim of the study was to determine data-driven decision-making among health providers, acase of Mombasa County, Kenya.Methods:The study employed an analytical cross-sectional study design where a stratified random sampling approach was utilized to recruit respondents into the study. The Yamane formula of sample size calculation was used to recruit 168 study partakers for this study.Results:The outcomes indicated that quality data-driven decision-making exhibited a substantial correlation withtechnical factors (r=0.642, p value=0.000). Furthermore, the findings highlighted a significant correlation between quality data-driven decision-making and behavioral factors (r=0.821, p value=0.000). Additionally, the study's results revealed a marked correlation between quality data-propelled decision-making alongside organizational factors (r=0.819, p value=0.000).Conclusions:The likelihood ratio tests demonstrated that both technical and organizational factors significantly predicted data-driven decision-making among health providers, whereas behavioral factors did not have a statistically significant impact. There is a need to provide training for health workers at the county level to enhance data utilization skills, ensure thorough data verification before submission, and promote the use of health information in decision-making
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    PublicationOpen Access
    Risk Factors Associated with Adverse Pregnancy Outcomes Among Women Who Were Attending Postnatal Services at Thika Level Five Hospital Kiambu County, Kenya
    (International Journal of Current Aspects, 2023-10-23) Eloi, Havyarimana; Nyamai, Joseph Juma; Mogere, Dominic
    Stillbirths, preterm deliveries and neonatal deaths are examples of adverse pregnancy and infant outcomes that continue to be a global public health problem. The World Health Organization (WHO), States, and non-governmental organizations (NGO) have invested a lot of time, money, and resources into promoting the benefits of safe pregnancy and delivery. Despite efforts to promote healthy pregnancy, delivery, and maternal mortality, these numbers continue to be high. Pregnant mothers and their fetusare put indanger due to several risk issues. Despite the limited data from Thika level five hospitals, concern about poor pregnancy outcomes have been growing. The study’s goal wasto pinpoint the risk factors connected to pregnancy outcomes atThika level five hospitals.Ananalytical cross-sectionalstudy was carried out on women between the age of 15 and 49 who were attending postnatal services at Thikalevel 5.The study usedqualitative andquantitative data collection techniques.80 samples were chosen out of 100 population. A Convenience sampling and purposive sampling were used.structured questionnaireswere used at thehealth care facility.The mean age was 15 to 19.Most of them were married almostboth living in urban and rural areas. According to education, most have reached college education but unfortunately,55% of them are unemployed and 51% of them are living in temporally house, most generating income below 5000. Most of them live 5km away from the nearest health facility.55% of them attendedantenatal and its essential services in public facilities, motivated by self-motives. 47% of the respondents delivered via spontaneous vertex delivery followed by 37% of caesarean sections. Most complicationswereobstructed laborand most adverse outcomeswerepreterm labor.The most common pre-existing medical conditions wereanemiaand HIV/AIDS. The most common adverse pregnancy outcome found in this study included PPH, Obstructed labor, APH, neonatal mortality, preterm babies, and stillbirth and low birth weight babies. Inferential statistics including correlation and bivariate analysis were used. The regression coefficients results portrays that socio-demographics characteristics score 0.983 with standard error of 0.361.Pre-existing medical conditions scored 0.897 with a standard error of 0.323. Intrapartum care scored 0.920 with a standard error of 0.240. Chi-square analysis for all the variables was calculated at 47.633 and the p value less than 0.05 (p< 0.05). Correlation study indicates a positive significance between pregnancy risk andsocio-demographics, pre-existing medical conditions with a value of 0.934. The researcher concludesthat numerouspregnancy problems arisefrom lack of medical knowledge and financial structure coming from the women whoarepregnant. Concluding to the fact that when it comes to risk in pregnancy there are a number of factors that come into play. This ranges from ages of the women to pre-existing medical conditions when it comes to childbirth. Overall it is highly important for women who are prone to have complications in child labor to International Journal of Current Aspects, Volume 7, Issue 3, 2023 PP 40-60, ISSN 2707-803541have medical checkupsconstantly so that any complications cane be dealt within a reasonable timeframe and with little consequences to the women or their unborn babies.