Improving Health Systems: Influence of Technical Capacities of Community Health Volunteers on Use of Community Health Information Systems in Kenya

Abstract

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