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.
Published in | World Journal of Public Health (Volume 9, Issue 2) |
DOI | 10.11648/j.wjph.20240902.11 |
Page(s) | 95-110 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Health System Strengthening, Health Management Information Systems (HMIS), Behavioural Factors, Community Health Promoters, Community Based Health Management Information Systems
[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. |
[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. |
[6] | Jeremie N., Kaseje, D., Olayo, R., & Akinyi, C. (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(4), 37–42. |
[7] | Kaburu, E., Kaburi, L., & Okero, D. (2016). Factors Influencing the Functionality of Community- Based Health Information Systems in Embakasi Sub- County, Nairobi County, Kenya. International Journal of Scientific and Research Publications, 6(5), 514-519. |
[8] | Kibua, T. N., Muia, D. M., & Keraka, M. (2009). Efficacy of Community Based health care in Kenya: An evaluation of AMREF's 30 years in Kibwezi. AMREF Discussion Paper Series. Retrieved from |
[9] | Kihara, P. (2016). Strategy Implementation and Performance of Manufacturing Firms in Kenya. Latvia, European Union: Lap Lambert Academic Publishing. |
[10] |
Lehmann, U., & Matwa, P. (2008). Exploring the concept of power in the implementation of South Africa’s new community health worker policies: A case study from a rural sub-district. Discussion paper 64. Retrieved from
http://www.equinetafrica.org/sites/default/files/uploads/documents/DIS64POLlehmann.pdf |
[11] | Mambo, S. N, Odhiambo-Otieno G. W, Ochieng’ Otieno G. and Wanja Mwaura T. (2021). Health systems strengthening: assessing the influence of organizational factors of community health volunteers on use of community based health information systems in selected counties, Kenya. International journal of community medicine and public health. |
[12] | Mambo, S. N, Odhiambo-Otieno G. W, Ochieng’ Otieno G. and Wanja Mwaura T. (2018). 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 (0975 – 8887) Volume 181 – No. 3, July 2018. |
[13] | Mambo, S. N, Odhiambo-Otieno G. W, Ochieng’ Otieno G. and Wanja Mwaura T. (2018). Assessing the influence of process interventions of community health volunteers on use of Community Based Health Management Information Systems in selected Counties, Kenya. |
[14] | Measure Evaluation (2009). Technical Consultation on Information Systems for Community-Based HIV Programs: MEASURE Evaluation. Retrieved August 30, 2017, from |
[15] |
Measure Evaluation. (2016). Community-based Health Information Systems in the Global Context: A Review of the Literature: MEASURE Evaluation. Retrieved March 26, 2018, from
https://www.measureevaluation.org/resources/publications/wp-16-161 |
[16] | Mbondenyi & Ambani (2014) The New Constitutional Law of Kenya. Principles, Government and Human Rights: Principles, Government and Human Rights. |
[17] | Ministry of Health (2008). Collect, Manage, Visualize and Explore your Data. Retrieved November 4, 2016, from |
[18] | Ministry of Health (2010). Microsoft Word - Community Strategy Evaluation report Retrieved November 4, 2016, from |
[19] | Ministry of Health (2016). Kenya Master Health Facility List: Find all the health facilities in Kenya. Retrieved November 4, 2016, from |
[20] | Mugenda, O., & Mugenda, A. (2003). Research Methods: Quantitative and Qualitative Approaches. Nairobi: ACTS. |
[21] |
Naikal, A., & Chandra, S. (2013). Organisational Culture: A Case Study. Retrieved November 7, 2016, from
https://www.researchgate.net/publication/260094253_Organisational_Culture_A_Case_Study |
[22] |
Nutley, T. (2012). Improving Data Use in Decision Making: An Intervention to Strengthen Health Systems: MEASURE Evaluation. Retrieved November 4, 2016, from
https://www.measureevaluation.org/resources/publications/sr-12-73 |
[23] | Nzinga, J., Mbaabu, L., & English, M. (2013). Service delivery in Kenyan district hospitals–what can we learn from literature on mid-level managers? Human Resources for Health, 11(1), 1. |
[24] | Odhiambo-Otieno, G. W., & Odero, W. W. (2005). Evaluation criteria for the district health management information systems: Lessons from the Ministry of Health, Kenya. African Health Sciences, 5(1), 59–64. |
[25] | Pepela, W., & Odhiambo-Otieno, G. (2016). Community health information system utility: A case of Bungoma County Kenya. International Research Journal of Public and Environmental Health, 3(4), 75-86. |
[26] | Vujicic, M., Ohiri, K., & Sparkes, S. (2009). Working in Health: Financing and Managing the Public Sector Health Workforce. Retrieved from |
[27] |
World Health Organization. (2007). Everybody’s business. Retrieved November 4, 2016, from
http://www.who.int/healthsystems/strategy/everybodys_business.pdf |
[28] |
World Health Organization. (2010). Monitoring the building blocks of health systems: A handbook of indicators and their measurement strategies. Retrieved November 4, 2016, from
http://www.who.int/healthinfo/systems/WHO_MBHSS_2010_full_web.pdf |
APA Style
Mambo, S. N., Odhiambo-Otieno, G., Ochieng’-Otieno, G., Mwaura-Tenambergen, W. (2024). 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, 9(2), 95-110. https://doi.org/10.11648/j.wjph.20240902.11
ACS Style
Mambo, S. N.; Odhiambo-Otieno, G.; Ochieng’-Otieno, G.; Mwaura-Tenambergen, W. Assessing the Influence of Behavioural Factors of Community Health Promoters on Use of Community Based Health Information Systems in Selected Counties, Kenya. World J. Public Health 2024, 9(2), 95-110. doi: 10.11648/j.wjph.20240902.11
AMA Style
Mambo SN, Odhiambo-Otieno G, Ochieng’-Otieno G, Mwaura-Tenambergen W. Assessing the Influence of Behavioural Factors of Community Health Promoters on Use of Community Based Health Information Systems in Selected Counties, Kenya. World J Public Health. 2024;9(2):95-110. doi: 10.11648/j.wjph.20240902.11
@article{10.11648/j.wjph.20240902.11, author = {Susan Njoki Mambo and George Odhiambo-Otieno and George Ochieng’-Otieno and Wanja Mwaura-Tenambergen}, title = {Assessing the Influence of Behavioural Factors of Community Health Promoters on Use of Community Based Health Information Systems in Selected Counties, Kenya }, journal = {World Journal of Public Health}, volume = {9}, number = {2}, pages = {95-110}, doi = {10.11648/j.wjph.20240902.11}, url = {https://doi.org/10.11648/j.wjph.20240902.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wjph.20240902.11}, 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 p2 = .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. }, year = {2024} }
TY - JOUR T1 - Assessing the Influence of Behavioural Factors of Community Health Promoters on Use of Community Based Health Information Systems in Selected Counties, Kenya AU - Susan Njoki Mambo AU - George Odhiambo-Otieno AU - George Ochieng’-Otieno AU - Wanja Mwaura-Tenambergen Y1 - 2024/04/28 PY - 2024 N1 - https://doi.org/10.11648/j.wjph.20240902.11 DO - 10.11648/j.wjph.20240902.11 T2 - World Journal of Public Health JF - World Journal of Public Health JO - World Journal of Public Health SP - 95 EP - 110 PB - Science Publishing Group SN - 2637-6059 UR - https://doi.org/10.11648/j.wjph.20240902.11 AB - 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 p2 = .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. VL - 9 IS - 2 ER -