Data Management Practices, Digitization, and Sustainability of Community Health Programmes in Nairobi County, Kenya
Authors
University of Nairobi (Kenya)
University of Nairobi (Kenya)
University of Nairobi (Kenya)
University of Nairobi (Kenya)
Article Information
DOI: 10.47772/IJRISS.2025.91100465
Subject Category: Public Health
Volume/Issue: 9/11 | Page No: 5900-5918
Publication Timeline
Submitted: 2025-12-04
Accepted: 2025-12-10
Published: 2025-12-18
Abstract
Monitoring and evaluation data from community health programs are essential for their planning, improvement, success, and sustainability. These data can inform implementers, policymakers, beneficiaries, and funders about the progress or lack of it, prompting them to take appropriate action at any stage of the project life cycle. This study examines the moderating influence of digitization on the relationship between data management practices and sustainability of community health programmes. The study is anchored on Technology Acceptance Model (TAM). A positivist philosophical paradigm and a cross-sectional descriptive survey research design to generate quantitative primary data. A Partial Least Squares – Structural Equation Model (PLS-SEM) priori sample size calculator was used to determine a sample size based on all observable variables, including measurement indicators for the moderating variables. The sample comprised 190 community health promoters in Nairobi County. The response rate was 83%. Data analysis was performed using SmartPLS 4. The study results affirmed that the impact of data management practices on the sustainability of community health programmes decreases with digitalisation. The results resonate with the TAM, which posits that the adoption of innovations, such as data management automation, is influenced by perceived benefits and ease of use for users. This study recommends a hybrid data management approach that combines traditional and automated practices to address the transition and the digital divide. The findings of this study can also be used by policymakers and programme implementers to design programmes with greater specificity about where to invest when introducing or scaling up data digitisation, as well as to address contextual factors that contribute to the sustainability of community health programmes
Keywords
Data management practices, Digitization, sustainability of community health programmes
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References
1. Åhlfeldt, E., Isaksson, D., & Winblad, U. (2023). Factors Explaining Program Sustainability: A Study of the Implementation of a Social Services Program in Sweden. Health & Social Care in the Community, 2023(1), 1458305. [Google Scholar] [Crossref]
2. Ahmed, I., & Ishtiaq, S. (2021). Reliability and Validity: Importance in Medical Research. Methods, 12(1), 2401-2406. [Google Scholar] [Crossref]
3. Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2019). PLS-SEM in information systems research: a comprehensive methodological reference. In Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 4 (pp. 644-653). Springer International Publishing. [Google Scholar] [Crossref]
4. Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the association for information systems, 8(4), 3. [Google Scholar] [Crossref]
5. Bahariniya, S., Ezatiasar, M., & Madadizadeh, F. (2021). A Brief Review of the Types of Validity and Reliability of Scales in Medical Research. Journal of Community Health Research, 10(2), 100-102. [Google Scholar] [Crossref]
6. Blondino, C. T., Knoepflmacher, A., Johnson, I., Fox, C., & Friedman, L. (2024). The use and potential impact of digital health tools at the community level: results from a multi-country survey of community health workers. BMC Public Health, 24(1), 650. [Google Scholar] [Crossref]
7. Bogale, T. N., Teklehaimanot, S. M., Fufa Debela, T., Enyew, D. B., Nigusse Bedada, A., Dufera Kebebew, S., ... & Bekele, T. A. (2023). Barriers, facilitators and motivators of electronic community health information system use among health workers in Ethiopia. Frontiers in Digital Health, 5, 1162239. [Google Scholar] [Crossref]
8. Bujang, M. A. (2021). A step-by-step process on sample size determination for medical research. The Malaysian journal of medical sciences: MJMS, 28(2), 15. [Google Scholar] [Crossref]
9. Ceptureanu, S. I., & Ceptureanu, E. G. (2019). Community-based healthcare programs sustainability impact on the sustainability of host organizations: A structural equation modeling analysis. International Journal of Environmental Research and Public Health, 16(20), 4035. [Google Scholar] [Crossref]
10. Chepkirui, M., Dellicour, S., Musuva, R., Odero, I., Omondi, B., Omondi, B., ... & Taegtmeyer, M. (2025). Missed opportunities for digital health data use in healthcare decision-making: A cross-sectional digital health landscape assessment in Homa Bay County, Kenya. PLOS Digital Health, 4(6), e0000870. [Google Scholar] [Crossref]
11. Chirambo, G. B., Hardy, V., Heavin, C., O’Connor, Y., O’Donoghue, J., Mastellos, N., ... & Thompson, M. (2018). Perceptions of a mobile health intervention for Community Case Management in Malawi: Opportunities and challenges for Health Surveillance Assistants in a community setting. Malawi Medical Journal, 30(1), 6-12. [Google Scholar] [Crossref]
12. Chirchir, M. K. (2022). Supply Chain Integration, Competitive Advantage, Environmental Dynamism and Performance of Large-Scale Manufacturing Firms in Kenya (Doctoral dissertation, University of Nairobi). [Google Scholar] [Crossref]
13. Collier, J. (2020). Applied structural equation modeling using AMOS: Basic to advanced techniques. Routledge. [Google Scholar] [Crossref]
14. Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205-219. [Google Scholar] [Crossref]
15. Demirci, H. F., & Yardan, E. D. (2023). Data management in the digital health environment scale development study. BMC Health Services Research, 23(1), 1249. [Google Scholar] [Crossref]
16. Dillip, A., Kahamba, G., Sambaiga, R., Shekalaghe, E., Kapologwe, N., Kitali, E., ... & Sarkar, N. (2024). Using digital technology as a platform to strengthen the continuum of care at community level for maternal, child and adolescent health in Tanzania: introducing the Afya-Tek program. BMC Health Services Research, 24(1), 865. [Google Scholar] [Crossref]
17. Donessouné, F. M., Sossa, G. O., & Kouanda, S. (2023). Sustainability of community health programme using community-based organizations: a challenge for stakeholders. BMC Health Services Research, 23(1), 1-11. [Google Scholar] [Crossref]
18. Fauzi, M. A. (2022). Partial Least Square Structural Equation Modelling (PLS-SEM) in Knowledge Management Studies: Knowledge Sharing in Virtual Communities. Knowledge Management & E-Learning, 14(1), 103-124. [Google Scholar] [Crossref]
19. Feroz, A., Jabeen, R., & Saleem, S. (2020). Using mobile phones to improve community health workers performance in low-and-middle-income countries. BMC public health, 20, 1-6. [Google Scholar] [Crossref]
20. Fitzpatrick, K. M., Ody, M., Goveas, D., Montesanti, S., Campbell, P., MacDonald, K., ... & Roach, P. (2023). Understanding virtual primary healthcare with Indigenous populations: a rapid evidence review. BMC Health Services Research, 23(1), 303. [Google Scholar] [Crossref]
21. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics: 382-388 [Google Scholar] [Crossref]
22. Habte, D., Zemenfeskudus, S., Endale, M., Zeidan, M., Getachew, D., Woldemichael, D., ... & Abayneh, S. A. (2022). Enhancing and promoting data management and systematic monitoring for an improved HIV/AIDS programs in Addis Ababa, Ethiopia. BMC Health Services Research, 22, 1-11. [Google Scholar] [Crossref]
23. Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. [Google Scholar] [Crossref]
24. Hujala, T., & Laihonen, H. (2021). Effects of knowledge management on the management of health and social care: a systematic literature review. Journal of knowledge management, 25(11), 203-221. [Google Scholar] [Crossref]
25. Hussein, S., Otiso, L., Kimani, M., Olago, A., Wanyungu, J., Kavoo, D., ... & Karuga, R. (2021). Institutionalizing community health services in Kenya: A policy and practice journey. Global Health: Science and Practice, 9(Supplement 1), S25-S31. [Google Scholar] [Crossref]
26. Jaja, I. R., Idoniboye, O., & Amadi, C. C. (2022). A Critique of the Positivist Paradigm in Human Sciences. International Journal of Research and Innovation in Social Science, 6(3), 224-229. [Google Scholar] [Crossref]
27. Jeilani, A., & Hussein, A. (2025). Impact of digital health technologies adoption on healthcare workers’ performance and workload: perspective with DOI and TOE models. BMC Health Services Research, 25(1), 271. [Google Scholar] [Crossref]
28. Kaboré, S. S., Ngangue, P., Soubeiga, D., Barro, A., Pilabré, A. H., Bationo, N., ... & Savadogo, G. B. L. (2022). Barriers and facilitators for the sustainability of digital health interventions in low and middle-income countries: a systematic review. Frontiers in digital health, 4, 1014375. [Google Scholar] [Crossref]
29. Kansiime, W. K., Atusingwize, E., Ndejjo, R., Balinda, E., Ntanda, M., Mugambe, R. K., & Musoke, D. (2024). Barriers and benefits of mHealth for community health workers in integrated community case management of childhood diseases in Banda Parish, Kampala, Uganda: a cross-sectional study. BMC Primary Care, 25(1), 173. [Google Scholar] [Crossref]
30. Khatri, R. B., Endalamaw, A., Erku, D., Wolka, E., Nigatu, F., Zewdie, A., & Assefa, Y. (2024). Enablers and barriers of community health programs for improved equity and universal coverage of primary health care services: A scoping review. BMC primary care, 25(1), 385. [Google Scholar] [Crossref]
31. Kirk, K., McClair, T. L., Dakouo, S. P., Abuya, T., & Sripad, P. (2021). Introduction of digital reporting platform to integrate community-level data into health information systems is feasible and acceptable among various community health stakeholders: A mixed-methods pilot study in Mopti, Mali. Journal of Global Health, 11. [Google Scholar] [Crossref]
32. Lee, J., Lynch, C. A., Hashiguchi, L. O., Snow, R. W., Herz, N. D., Webster, J., ... & Erondu, N. A. (2021). Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review. BMJ global health, 6(6). [Google Scholar] [Crossref]
33. Mehra, R., Boyd, L. M., Lewis, J. B., & Cunningham, S. D. (2020). Considerations for building sustainable community health worker programs to improve maternal health. Journal of Primary Care & Community Health, 11, 2150132720953673. [Google Scholar] [Crossref]
34. Ministry of Health, Division of Community Health Services, Republic of Kenya (2021). Kenya Community Health Policy 2020 – 2030. Nairobi, Kenya. https://www.health.go.ke/ [Google Scholar] [Crossref]
35. Ministry of Health, Division of Community Health Services, Republic of Kenya (2019). Kenya Community Health Strategy 2020 – 2025. Nairobi, Kenya. https://www.health.go.ke/ [Google Scholar] [Crossref]
36. Ministry of Health, Division of Community Health Services, Republic of Kenya (2021). National Community Health Digitization Strategy 2020-2025. Nairobi, Kenya. https://www.health.go.ke/ [Google Scholar] [Crossref]
37. Ministry of Health. (2020). Kenya Community Health Policy 2020–2030. Nairobi. [Google Scholar] [Crossref]
38. Mohd Dzin, N. H., & Lay, Y. F. (2021). Validity and reliability of adapted self-efficacy scales in Malaysian context using PLS-SEM approach. Education Sciences, 11(11), 676. [Google Scholar] [Crossref]
39. Mremi, I. R., Sindato, C., Kishamawe, C., Rumisha, S. F., Kimera, S. I., & Mboera, L. E. (2022). Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania. Global Health Action, 15(1), 2090100. [Google Scholar] [Crossref]
40. Muinga, N., Magare, S., Monda, J., English, M., Fraser, H., Powell, J., & Paton, C. (2020). Digital health Systems in Kenyan Public Hospitals: a mixed-methods survey. BMC medical informatics and decision making, 20(1), 2. [Google Scholar] [Crossref]
41. Njororai, F., Ganu, D., Nyaranga, K. C., & Wilberforce, C. (2021). Role of socio-demographic and environmental determinants on performance of community health Workers in Western Kenya. International Journal of Environmental Research and Public Health, 18(21), 11707. [Google Scholar] [Crossref]
42. Numair, T., Harrell, D. T., Huy, N. T., Nishimoto, F., Muthiani, Y., Nzou, S. M., ... & Kaneko, S. (2021). Barriers to the digitization of health information: a qualitative and quantitative study in Kenya and Lao PDR using a cloud-based maternal and child registration system. International Journal of Environmental Research and Public Health, 18(12), 6196. [Google Scholar] [Crossref]
43. Nyimbili, L., & Chalwe, M. (2023). A Review of Technology Acceptance and Adoption Models and Theories. International Journal for Multidisciplinary Research (IJFMR), 5(6), 1-10. [Google Scholar] [Crossref]
44. Odock, S. O. (2016). Green supply chain management practices and performance of ISO 14001 certified manufacturing firms in East Africa (Doctoral dissertation, University of Nairobi). [Google Scholar] [Crossref]
45. Ogutu, M., Muraya, K., Mockler, D., & Darker, C. (2021). Factors influencing the performance of community health volunteers working within urban informal settlements in low-and middle-income countries: a qualitative meta-synthesis review. Human resources for health, 19, 1-21. [Google Scholar] [Crossref]
46. Owoyemi, A., Osuchukwu, J. I., Azubuike, C., Ikpe, R. K., Nwachukwu, B. C., Akinde, C. B., ... & Olaniran, S. (2022). Digital solutions for community and primary health workers: lessons from implementations in Africa. Frontiers in Digital Health, 4, 876957. [Google Scholar] [Crossref]
47. Park, Y. S., Konge, L., & Artino Jr, A. R. (2020). The positivism paradigm of research. Academic medicine, 95(5), 690-694. [Google Scholar] [Crossref]
48. Perry, H. B., Chowdhury, M., Were, M., LeBan, K., Crigler, L., Lewin, S., ... & Hodgins, S. (2021). Community health workers at the dawn of a new era: 11. CHWs leading the way to “Health for All”. Health Research Policy and Systems, 19, 1-21. [Google Scholar] [Crossref]
49. Popa, I., & Ștefan, S. C. (2019). Modeling the pathways of knowledge management towards social and economic outcomes of health organizations. International journal of environmental research and public health, 16(7), 1114. [Google Scholar] [Crossref]
50. Ramli, N. A., Latan, H., & Nartea, G. V. (2018). Why should PLS-SEM be used rather than regression? Evidence from the capital structure perspective. Partial least squares structural equation modeling: Recent advances in banking and finance, 171-209. [Google Scholar] [Crossref]
51. Regeru, R. N., Chikaphupha, K., Bruce Kumar, M., Otiso, L., & Taegtmeyer, M. (2020). ‘Do you trust those data?’—a mixed-methods study assessing the quality of data reported by community health workers in Kenya and Malawi. Health Policy and Planning, 35(3), 334-345. [Google Scholar] [Crossref]
52. Rîndaşu, S. M., Ionescu-Feleagă, L., Ionescu, B. Ş., & Topor, I. D. (2023). Digitalisation and skills adequacy as determinants of innovation for sustainable development in EU countries: a PLS-SEM approach. Amfiteatru Economic, 25, 968-986. [Google Scholar] [Crossref]
53. Russpatrick, S., Li, M., Braa, J., Bruland, A., Rodvelt, M. O., Muhire, A., ... & Rustad, S. (2021). Improving Data Use and Participatory Action and Design to Support Data Use: The Case of DHIS2 in Rwanda. arXiv preprint arXiv:2108.09721. [Google Scholar] [Crossref]
54. Saade, R., Nebebe, F., Mak, T., & Leung, N. K. (2011). Knowledge management systems development: Theory and practice. Interdisciplinary Journal of Information, Knowledge & Management, 6. [Google Scholar] [Crossref]
55. Sabol, M., Hair, J., Cepeda, G., Roldán, J. L., & Chong, A. Y. L. (2023). PLS-SEM in information systems: seizing the opportunity and marching ahead full speed to adopt methodological updates. Industrial Management & Data Systems, 123(12), 2997-3017. [Google Scholar] [Crossref]
56. Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Cham: Springer International Publishing. [Google Scholar] [Crossref]
57. Shanmuganathan, S., Mustapha, F. I., & Wilson, A. (2022). Evaluating the sustainability of non-communicable diseases programs in Malaysia. BMC Public Health, 22(1), 1463. [Google Scholar] [Crossref]
58. Silva, P. (2015). Davis' technology acceptance model (TAM)(1989). Information seeking behavior and technology adoption: Theories and trends, 205-219. [Google Scholar] [Crossref]
59. Soper, D. S. (2020). A-priori sample size calculator for structural equation models [Software]. https://www.danielsoper.com/statcalc/calculator.aspx?id=89 [Google Scholar] [Crossref]
60. Tamrat, T., Chandir, S., Alland, K., Pedrana, A., Shah, M. T., Footitt, C., ... & Mehl, G. L. (2022). Digitalization of routine health information systems: Bangladesh, Indonesia, Pakistan. Bulletin of the World Health Organization, 100(10), 590. [Google Scholar] [Crossref]
61. Taris, T. W., Kessler, S. R., & Kelloway, E. K. (2021). Strategies addressing the limitations of cross-sectional designs in occupational health psychology: What they are good for (and what not). Work & Stress, 35(1), 1-5. [Google Scholar] [Crossref]
62. Tshuma, N., Elakpa, D. N., Moyo, C., Soboyisi, M., Moyo, S., Mpofu, S., ... & Mtapuri, O. (2024). The transformative impact of community-led monitoring in the South African health system: a comprehensive analysis. International Journal of Public Health, 69, 1606591. [Google Scholar] [Crossref]
63. Unkels, R., Manzi, F., Kapologwe, N. A., Baker, U., Ahmad, A., Nabiev, R., ... & Hirose, A. (2023). Feasibility, usability and acceptability of a novel digital hybrid-system for reporting of routine maternal health information in Southern Tanzania: A mixed-methods study. PLOS Global Public Health, 3(1), e0000972. [Google Scholar] [Crossref]
64. World Health Organization (2020). Health policy and system support to optimize community health worker programmes for HIV, TB and malaria services: an evidence guide. Geneva: Licence: CC BY-NC-SA 3.0 IGO. https://iris.who.int/bitstream/handle/10665/340078/9789240018082-eng.pdf?sequence=1 [Google Scholar] [Crossref]
65. Yang, J. E., Lassala, D., Liu, J. X., Whidden, C., Holeman, I., Keita, Y., ... & Johnson, A. D. (2021). Effect of mobile application user interface improvements on minimum expected home visit coverage by community health workers in Mali: a randomised controlled trial. BMJ global health, 6(11), [Google Scholar] [Crossref]
66. Zaidi, S., Kazi, A. M., Riaz, A., Ali, A., Najmi, R., Jabeen, R., ... & Sayani, S. (2020). Operability, usefulness, and task-technology fit of an mhealth app for delivering primary health care services by community health workers in underserved areas of Pakistan and Afghanistan: Qualitative study. Journal of Medical Internet Research, 22(9), e18414. [Google Scholar] [Crossref]
67. Zeleke, A. A., Worku, A. G., Demissie, A., Otto-Sobotka, F., Wilken, M., Lipprandt, M., ... & Röhrig, R. (2019). Evaluation of electronic and paper-pen data capturing tools for data quality in a public health survey in a health and demographic surveillance site, Ethiopia: randomized controlled crossover health care information technology evaluation. JMIR mHealth and uHealth, 7(2), e10995 [Google Scholar] [Crossref]
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