CFP last date
22 April 2024
Reseach Article

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

by Susan Njoki Mambo, George W. Odhiambo-Otieno, George Ochieng'-Otieno, Wanja Mwaura-Tenermbergen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 3
Year of Publication: 2018
Authors: Susan Njoki Mambo, George W. Odhiambo-Otieno, George Ochieng'-Otieno, Wanja Mwaura-Tenermbergen
10.5120/ijca2018917458

Susan Njoki Mambo, George W. Odhiambo-Otieno, George Ochieng'-Otieno, Wanja Mwaura-Tenermbergen . 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. 181, 3 ( Jul 2018), 30-37. DOI=10.5120/ijca2018917458

@article{ 10.5120/ijca2018917458,
author = { Susan Njoki Mambo, George W. Odhiambo-Otieno, George Ochieng'-Otieno, Wanja Mwaura-Tenermbergen },
title = { Improving Health Systems: Influence of Technical Capacities of Community Health Volunteers on Use of Community Health Information Systems in Kenya },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 181 },
number = { 3 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 30-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number3/29699-2018917458/ },
doi = { 10.5120/ijca2018917458 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:04:55.460120+05:30
%A Susan Njoki Mambo
%A George W. Odhiambo-Otieno
%A George Ochieng'-Otieno
%A Wanja Mwaura-Tenermbergen
%T Improving Health Systems: Influence of Technical Capacities of Community Health Volunteers on Use of Community Health Information Systems in Kenya
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 3
%P 30-37
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
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 cross-sectional 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 (R2 =.286). This implies that the use of CBHMIS by Community Units (CU) improves significantly when the CU personnel have better technical capacities.

References
  1. Aqil, Anwer, Theo Lippeveld, and Dairiku Hozumi (2009)“PRISM Framework: A Paradigm Shift for Designing, Strengthening and Evaluating Routine Health Information Systems.” Health Policy and Planning 24, no. 3 (May 2009): 217–28. https://doi.org/10.1093/heapol/czp010.
  2. Abajebel, S., Jira, C., &amp; Beyene, W. (2011). Utilization of Health Information System at District Level in Jimma Zone Oromia Regional State, South West Ethiopia. Ethiopian Journal of Health Sciences, 21(Suppl 1), 65–76.
  3. Amref Kenya. (2014, June 4). Community Based Health Management Information System (CBHMIS) “Taarifa” Project (Jan-2013 – Dec-2015). Retrieved November 4, 2016, from https://amrfhrtg.wordpress.com/2014/06/04/community-based-health-management-information-system-cbhmis-taarifa-project/
  4. Berkman, N. D., Dewalt, D. A., Pignone, M. P., Sheridan, S. L., Lohr, K. N., Lux, L., … Bonito, A. J. (2004). Literacy and Health Outcomes: Summary. Agency for Healthcare Research and Quality (US). Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK11942/
  5. Cheburet, Samuel, and G.W Odhiambo-Otieno. (2016) “Process Factors Influencing Data Quality,” 2016a. http://journalissues.org/wp-content/uploads/2016/06/ International Research Journal of Public and Environmental Health Vol.3 (6),pp. 132-139, June 2016.
  6. Cheburet-and-Odhiambo-Otieno.pdf.(2016) “State of Data Quality of Routing Health Management Information System: Case of Uasin Gishu County Referral Hospi Tal, Kenya,” 2016b. http://journalissues.org/wp-content/uploads/2016/08/Cheburet-and-Odhiambo-Otieno.pdf. International Research Journal of Public and Environmental Health Vol.3 (6),pp. 132-139, June 2016.
  7. chewicha, K. (2013)“Community Health Information System for Family-Centered Health Care: Scale-up in Southern Nations, Nationalities and People’s Region — MEASURE Evaluation.” Publication, 2013. https://www.measureevaluation.org/resources/publications/ja-13-161.
  8. Jeremie, Nzanzu, Dan Kaseje, Rose Olayo, and Caroline Akinyi.(2014) “Utilization of Community-Based Health Information Systems in Decision Making and Health Action in Nyalenda, Kisumu County, Kenya.” Universal Journal of Medical Science 2, no. 4 (2014): 37–42.
  9. Health Metrics Network, &amp; World Health Organization (Eds.). (2008). Assessing the national health information system: an assessment tool (Version 4.00). Geneva: World Health Organization.
  10. Kaburu, E., Kaburi, L., &amp; Okero, D. (2016). Factors Influencing the Functionality of Community- Based Health Information Systems in Embakasi Sub- County, Nairobi County, Kenya | Qualitative Research | Quantitative Research. Retrieved March 19, 2018, from https://www.scribd.com/document/315323806/Factors-Influencing-the-Functionality-of-Community-Based-Health-Information-Systems-in-Embakasi-Sub-County-Nairobi-County-Kenya
  11. Kibua, T. N., Muia, D. M., &amp; Keraka, M. (2009). AMREF Discussion Paper Series.
  12. LaTour, K. M., &amp; Eichenwald, S. (2002). Health Information Management: Concepts, Principles, and Practice. Chicago, Ill: American Health Information Management Associ.
  13. Mesquita, A. (2012). User Perception and Influencing Factors of Technology in Everyday Life (1 edition). Hershey, PA: IGI Global.
  14. Ministry of Health, K. (2008). Collect, Manage, Visualize and Explore your Data. Retrieved November 4, 2016, from https://www.dhis2.org/
  15. Ministry of Health, K. (2010). Microsoft Word - Community Strategy Evaluation report October 2010.doc - 14_2010_HE_002_Community_Strategy_Evaluation_report_October_2010.pdf. Retrieved November 4, 2016, from http://www.unicef.org/evaldatabase/files/14_2010_HE_002_Community_Strategy_Evaluation_report_October_2010.pdf
  16. Karuri, Josephine, Peter Waiganjo, ORWA Daniel, and Ayub MANYA.(2014) “DHIS2: The Tool to Improve Health Data Demand and Use in Kenya.” Journal of Health Informatics in Developing Countries 8, no. 1 (2014). http://jhidc.org/index.php/jhidc/article/view/113.
  17. Lenette, Golding. “Strengthening_Community_Health_Systems_through_CHWs_and_mHealth.pdf,” 2014. http://www.coregroup.org/storage/documents/Fall_Conference_2014/Strengthening_Community_Health_Systems_through_CHWs_and_mHealth.pdf.
  18. Measure, Evaluation. (2009) “Technical Consultation on Information Systems for Community-Based HIV Programs — MEASURE Evaluation,” 2009. https://www.measureevaluation.org/our-work/hiv-aids/community-based-hiv-info-systems/hiv-meeting-registration/folder_contents?show_all=true.
  19. Ministry of Health, Kenya. (2016)“Collect, Manage, Visualize and Explore Your Data,” 2008. https://www.dhis2.org/. “Kenya Master Health Facility List: Find All the Health Facilities in Kenya,” nd 2016. http://kmhfl.health.go.ke/#/home.“Microsoft Word - Community Strategy Evaluation Report October 2010.doc - 14_2010_HE_002_Community_Strategy_Evaluation_report_October_2010.pdf,” 2010. http://www.unicef.org/evaldatabase/files/14_2010_HE_002_Community_Strategy_Evaluation_report_October_2010.pdf.
  20. Nutley, T.(2012) “Improving Data Use in Decision Making: An Intervention to Strengthen Health Systems — MEASURE Evaluation.” Publication, 2012. https://www.measureevaluation.org/resources/publications/sr-12-73.
  21. Odhiambo-Otieno, George W, and Wilson WO Odero.(2005) “Evaluation Criteria for the District Health Management Information Systems: Lessons from the Ministry of Health, Kenya.” African Health Sciences 5, no. 1 (March 2005): 59–64.
  22. Pepela, Wanjala, and G.W Odhiambo-Otieno.(2016) “Community Health Information System Utility: A Case of Bungoma C Ounty Kenya,” 2016. http://journalissues.org/wp-content/uploads/2016/04/Pepela-and-Odhiambo-Otieno.pdf.
  23. Sharma, Reetu, Premila Webster, and Sanghita Bhattacharyya.(2014) “Factors Affecting the Performance of Community Health Workers in India: A Multi-Stakeholder Perspective.” Global Health Action 7, no. 0 (October 13, 2014). https://doi.org/10.3402/gha.v7.25352.
  24. World Health Organization.(2010) “WHO_MBHSS_2010_full_web.pdf,” 2010. http://www.who.int/healthinfo/systems/WHO_MBHSS_2010_full_web.pdf.
  25. World Health Organization. (2007). everybodys_business.pdf. Retrieved November 4, 2016, from http://www.who.int/healthsystems/strategy/everybodys_business.pdf
Index Terms

Computer Science
Information Sciences

Keywords

Health Systems Strengthening Community Based – Health Management Information system Use of CBHMIS Technical capacity factors.