Browsing by Author "Mambo, Susan Njoki"

Now showing 1 - 4 of 4
  • No Thumbnail Available
    Item
    Assessing the Influence of Behavioural Factors of Community Health Promoters on Use of Community Based Health Information Systems in Selected Counties, Kenya
    (World Journal of Public Health, 2024-04-28) Mambo, Susan Njoki; Odhiambo-Otieno, George W.; Ochieng’-Otieno, George; Tenambergen, Mwaura Wanja
    Globally, health management information systems (HMIS) in strengthening health systems have gained recognition due to potential of technology to improve access to quality care in underserved communities. In Kenya, the functionality of Community based- Health Management Information System (CBHMIS) currently stands at 55% down from 64% in year 2015. The aim of this paper was to determine the influence of behavioral factors of community units personnel on CBHMIS. As a nested study, with a broader aimt to establish the operational status of CBHMIS and its use in selected counties in Kenya; The main objective of this research was: To establish whether behavioural factors of Community Health Promoters (CHPs) influence CBHMIS use in Kenya. A mixed method design. was adopted, Kiambu, Kajiado and Nairobi counties formed the study location, a target population of 156 active community units was considered to arrive at a total sample of 122 community units and out of 7800CHPs a sample of 366 respondents was drawn. Multistage sampling was used to identify the CUs, and systematic random sampling to identify 366 respondents. Quantitative data tools were semi-structured closed ended questionnaires. Qualitative data tools included observation checklist, Focus Group Discussion and Key Informant Interviews guides. Quantitative data was analyzed using SPSS to generate univariate and bivariate analysis at p<0.05 significance level; Qualitative data was analyzed using content analysis based on key themes generated from the objectives. Results were presented in form of graphs, tables, figures, and narration. This study showed that the use of Community based- Health Management Information System stood at 56.6%. Behavioural factors were found to significantly influence use of Community based- Health Management Information System. Further, of the total variations in the use of Community based- Health Management Information System, behavioral factor explains 13.7% (R2 = .137). Results show that the model was valid (F(1, 363) = 58.579, P = .001) hence the explanatory variable (X2, Behavioral factors) is good in explaining total variations in Use of CbHMIS by community units. This implies that the use of CbHMIS by Community Units (CU) improves significantly when the community units have better behavioural factors. In conclusion, behavioural factors of CHPs have strong and significant influence on the CBHMIS use. Motivation of CHPs is key as a motivator to CBHMIS use, as well as. provision of material support including reporting tools and IEC materials and capacity development technical, computer and electronic reporting skills to enhamce CHP operations and processes.
  • No Thumbnail Available
    Item
    Assessing the Influence of Process Interventions of Community Health Volunteers on Use of Community Based Health Management Information Systems in Selected Counties, Kenya.
    (International Journal of Scientific and Research Publications, 2018-08) Mambo, Susan Njoki; Odhiambo-Otieno, George W.; Ochieng’-Otieno, George; Tenambergen, Mwaura Wanja
    The World Health Organization (WHO) identified information as one of the six key pillars of an effective health system. In this context, the need to strengthen community health information has been felt globally. African countries have faced the greatest challenges in collecting, analyzing, evaluating and interpreting indicator data to guide evidence based policy-making. The generation of health information starts at the community level through the Community-Based health information system (CbHMIS) (Kaburu, Kaburi, & Okero, 2016). At the community level, this source of information is complete in coverage and in planning and action-oriented (Odhiambo-Otieno, 2005). High health threats characterized by low levels of life expectancy, deteriorating healthcare facilities, high disease incidences, high levels of infant mortality (73/1000) and maternal mortality (488/100,000) specifically on communicable diseases are currently facing Kenya (Flora, Margaret, & Dan, 2017). The importance of effective information use is still a key impediment to these problems, hence affecting greatly the health care service delivery at all levels, and the worst level in its information use is level 1 – the community. In Kenya, According to a situation analysis on the state of Community Health Services in year 2014, the functionality of CbHIS was said to be at 64% which came down considerably to 55% in year 2015 documented by USAID, and that access to quality data was not guaranteed through the current CbHMIS. Some known and assumed barriers include: lack of proper processes, lack of physical access, lack of awareness of what is available; lack of relevance of available information (i.e. not meeting peoples' needs in terms of scope, style or format); lack of time and incentives to access information; and lack of interpretation skills (Flora et al., 2017). Processes forms an integral part of performance (Aqil et al., 2009). In Kenya, the Kenyan Health Information System has had several weaknesses which include weak linkages, data sharing, inadequate feedback, and lack of an operational CBHMIS manual, among others. The purpose of the study was to assess the influence of process interventions of the CHVs on CBHIS use in Kiambu, Kajiado and Nairobi Counties, Kenya. The study objectives were to 1. examine the influence community units assesments on CbHMIS use; 2. Assess the influence of feedback on CbHMIS use; 3. Assess dialogue and action days influence on CbHMIS use; 4. Determine the influence of reporting channels on CbHMIs use. A cross-sectional analytical study design was adopted, utilizing both quantitative and qualitative approaches. The target population was 156 active CUs from the 3 counties, from whence a total sample of 122 CUswasderived. Multistage sampling was used to identify the CUs, and systematic random sampling to identify 366 respondents. One Focus Group Discussion with the members of the community health committees and two Key Informant Interviews (KIIs) were conducted in each of the three counties. The respondents in the KIIs were County Community Strategy Coordinators and Sub-county Community Strategy Officers. Quantitative data was analyzed using SPSS to generate univariate and bivariate analysis at p<0.05 significance level and results were presented in form of graphs, frequency tables, figures, and narration. Qualitative data was analyzed using content analysis based on key themes generated from the objectives. Majority were Females 72.4% n=265; majority attained secondary level education 42.6% (n=156); Non-formal occupation stood at 84.7% (n=310); Use of CBHMIS stood at 56.6% (n=207). Process interventions, 36% of the respondents agreed that the Sub-county team and CU leadership are quick to act on the feedback of our MIS reports. Process interventions (X4) explains 67.4% of total variation in CbHMIS use. (R2 = .674). Attention should be given to reporting channels by ensuring that CUs are technologically enabled to be reporting in a timely manner The study recommends that CUs should be provided with enabling technology and further capacity development in technical, computer and electronic reporting skills
  • No Thumbnail Available
    Item
    Improving Health Systems: Influence of Technical Capacities of Community Health Volunteers on Use of Community Health Information Systems in Kenya
    (International Journal of Computer Applications, 2018-07) Mambo, Susan Njoki; Odhiambo-Otieno, George W.; Ochieng’-Otieno, George; Tenambergen, Mwaura Wanja
    WHO identified six key pillars of an effective health system namely: leadership and governance; service delivery; health workforce; health information systems; medical products, vaccines and technologies and healthcare financing. This study focused on Community-based Health Management Information System (CbHMIS) of health information pillar. A Community-based Health Management Information System (CbHMIS) is a type of health information system based in the rural community and informal settlements of urban areas. CbHMIS’s main objective among others is to produce relevant and quality information to support decision making on public health issues at the community level. The importance of effective information use is still a key impediment to achievement of goals at level one of health care delivery. According to a situation analysis on the state of Community Health Services in year 2014, the functionality of CbHMIS was said to be at 64% which came down considerably to 55% in year 2015 documented by USAID, and that access to quality data was not guaranteed through the current CbHMIS.Lack of technical capacities among the CHVs is a serious gap in achievement of information use in Kenya.This study aimed at establishing the factors influencing technical capacities of community health volunteers on use of CbHMIS in Kenya.Other objectives of this study were: To establish the influence of System Availability on CbHMIS use; to find out effects of availability of skills to CHVs on CbHMIS use, To assess the influence of personnel knowledge on CbHMIS use, To identify competencies of CHVs that influence CbHMIS use. The selected counties were Kiambu, Kajiado and Nairobi which gave a rural, urban and peri-urban representation respectively of the country. This was a crosssectional analytical study design, with both quantitative and qualitative data collection methods. The target population was 156 active Community Units (CUs) from the 3 counties where a total sample of 122CUs (50 in Kiambu; 26 from Kajiado and 46 from Nairobi CUs) was derived using Mugenda and Mugenda formula of populations less than 10,000. Multistage sampling was used to identify the CUs; Systematic random sampling was used to identify total of 366 respondents 3Community Health Volunteers (CHVs) were purposively sampled form each CU to make a total of 366 (150 in Kiambu; 78 from Kajiado and 138 from Nairobi. A total of 6 KIIs (two from each county) and 3 FGDs (one from each county) were conducted for qualitative data. Interviewer administered questionnaires were used to collect quantitative data, observation checklist was also used. Quantitative data was analyzed using SPSS to generate univariate and bivariate analysis at p<0.05 significance level. Qualitative data was analyzed using content analysis based on key themes generated from the objectives. Results were presented in form of graphs, tables, figures, and narration. Use of Cb-HMIS stood at 56.6%. Slightly above half 51% of respondents agreed to having technical skills on CbHMIS, However a KII noted that “….We have challenges in training all our CHVs and refresher trainings due to funding so you will find some have been partially trained….”.There was statistical significant differences between group means (F(2,363) = 32.47,p = .000). (X1) explains 28.6% of the total variations in the use of CbHMIS (R 2 =.286). This implies that the use of CBHMIS by Community Units (CU) improves significantly when the CU personnel have better technical capacities. URI
  • No Thumbnail Available
    Item
    Improving Health Systems: Influence of Technical Capacities of Community Health Volunteers on Use of Community Health Information Systems in Kenya
    (International Journal of Computer Applications, 2018-07) Mambo, Susan Njoki; Odhiambo-Otieno, George W.; Ochieng’-Otieno, George; Tenambergen, Mwaura Wanja
    WHO identified six key pillars of an effective health system namely: leadership and governance; service delivery; health workforce; health information systems; medical products, vaccines and technologies and healthcare financing. This study focused on Community-based Health Management Information System (CbHMIS) of health information pillar. A Community-based Health Management Information System (CbHMIS) is a type of health information system based in the rural community and informal settlements of urban areas. CbHMIS’s main objective among others is to produce relevant and quality information to support decision making on public health issues at the community level. The importance of effective information use is still a key impediment to achievement of goals at level one of health care delivery. According to a situation analysis on the state of Community Health Services in year 2014, the functionality of CbHMIS was said to be at 64% which came down considerably to 55% in year 2015 documented by USAID, and that access to quality data was not guaranteed through the current CbHMIS.Lack of technical capacities among the CHVs is a serious gap in achievement of information use in Kenya.This study aimed at establishing the factors influencing technical capacities of community health volunteers on use of CbHMIS in Kenya.Other objectives of this study were: To establish the influence of System Availability on CbHMIS use; to find out effects of availability of skills to CHVs on CbHMIS use, To assess the influence of personnel knowledge on CbHMIS use, To identify competencies of CHVs that influence CbHMIS use. The selected counties were Kiambu, Kajiado and Nairobi which gave a rural, urban and peri-urban representation respectively of the country. This was a crosssectional analytical study design, with both quantitative and qualitative data collection methods. The target population was 156 active Community Units (CUs) from the 3 counties where a total sample of 122CUs (50 in Kiambu; 26 from Kajiado and 46 from Nairobi CUs) was derived using Mugenda and Mugenda formula of populations less than 10,000. Multistage sampling was used to identify the CUs; Systematic random sampling was used to identify total of 366 respondents 3Community Health Volunteers (CHVs) were purposively sampled form each CU to make a total of 366 (150 in Kiambu; 78 from Kajiado and 138 from Nairobi. A total of 6 KIIs (two from each county) and 3 FGDs (one from each county) were conducted for qualitative data. Interviewer administered questionnaires were used to collect quantitative data, observation checklist was also used. Quantitative data was analyzed using SPSS to generate univariate and bivariate analysis at p<0.05 significance level. Qualitative data was analyzed using content analysis based on key themes generated from the objectives. Results were presented in form of graphs, tables, figures, and narration. Use of Cb-HMIS stood at 56.6%. Slightly above half 51% of respondents agreed to having technical skills on CbHMIS, However a KII noted that “….We have challenges in training all our CHVs and refresher trainings due to funding so you will find some have been partially trained….”.There was statistical significant differences between group means (F(2,363) = 32.47,p = .000). (X1) explains 28.6% of the total variations in the use of CbHMIS (R 2 =.286). This implies that the use of CBHMIS by Community Units (CU) improves significantly when the CU personnel have better technical capacities