Assessing the Influence of Behavioural Factors of Community Health Promoters on Use of Community Based Health Information Systems in Selected Counties, Kenya

Author:

Mambo Susan1ORCID,Odhiambo-Otieno George2,Ochieng’-Otieno George3,Mwaura-Tenambergen Wanja3

Affiliation:

1. Department of Environmental Health and Disease Control, Jomo Kenyatta University of Agriculture and Technology, Juja, Kenya; Department of Health Systems Management, Kenya Methodist University, Meru, Kenya

2. Department of Health Sciences, Rongo University, Rongo, Kenya

3. Department of Health Informatics and Information Systems, Kenyatta University, Nairobi, Kenya

Abstract

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% (R<sup>2</sup> = .137). Results show that the model was valid (F<sub>(1, 363)</sub> = 58.579, <I>P </I>= .001) hence the explanatory variable (X<sub>2</sub>, 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.

Publisher

Science Publishing Group

Reference28 articles.

1. Aqil, A., Lippeveld, T., & Hozumi, D. (2009). PRISM framework: A paradigm shift for designing, strengthening and evaluating routine health information systems. Health Policy and Planning, 24(3), 217–228. https://doi.org/10.1093/heapol/czp010

2. Cheburet, S., & Odhiambo-Otieno, G. (2016b). State of data quality of routing Health Management Information System: Case of Uasin Gishu County Referral Hospi tal, Kenya. International Research Journal of Public and Environmental Health, 3 (8), 174-181.

3. Chewicha, K. (2013). Community Health Information System for Family-centered Health Care: Scale-up in Southern Nations, Nationalities and People’s Region — MEASURE Evaluation. Retrieved August 30, 2017, from https://www.measureevaluation.org/resources/publications/ja-13-161

4. Gilson, L., Daire, J., Patharath, A., & English, R. (2011). Leadership and governance within the South African health system. Durban: Health Systems Trust.

5. Haijden, J. G. (2009). Designing Management Information Systems. Oxford: Oxford University Press.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3