Determinants of data-driven decision-making among health providers: a case of Mombasa county, Kenya


  • Sally Wangige Muhula Department of Public Health, Mount Kenya University, Nairobi, Kenya
  • Joseph Juma Nyamai Department of Public Health, Mount Kenya University, Nairobi, Kenya
  • Alfred Owino Odongo Department of Public Health, Mount Kenya University, Nairobi, Kenya
  • Peterson Kariuki Department of Public Health, Mount Kenya University, Nairobi, Kenya



Health care providers, Health information management, Data-driven decision making


Background: Healthcare professionals understand how important it is to turn health data into information for informed decision-making. However, a lack of trustworthy and up-to-date health information is caused by inadequate investment in infrastructure for data collection, analysis, dissemination, and use. The aim of the study was to determine data-driven decision-making among health providers, a case of Mombasa County, Kenya.

Methods: The study employed an analytical cross-sectional study design where a stratified random sampling approach was utilized to recruit respondents into the study. The Yamane formula of sample size calculation was used to recruit 168 study partakers for this study.

Results: The outcomes indicated that quality data-driven decision-making exhibited a substantial correlation with technical factors (r=0.642, p value=0.000). Furthermore, the findings highlighted a significant correlation between quality data-driven decision-making and behavioral factors (r=0.821, p value=0.000). Additionally, the study's results revealed a marked correlation between quality data-propelled decision-making alongside organizational factors (r=0.819, p value=0.000).

Conclusions: The likelihood ratio tests demonstrated that both technical and organizational factors significantly predicted data-driven decision-making among health providers, whereas behavioral factors did not have a statistically significant impact. There is a need to provide training for health workers at the county level to enhance data utilization skills, ensure thorough data verification before submission, and promote the use of health information in decision-making.


Wagenaar BH, Hirschhorn LR, Henley C, Gremu A, Sindano N, Chilengi R, et al. Data-driven quality improvement in low-and middle-income country health systems: lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia. BMC Health Serv Res. 2017;17(3):830.

Krumholz HM. The Promise of Big Data: Opportunities and Challenges. Circ Cardiovasc Qual Outcomes. 2016;9(6):616-7.

Muinga N, Magare S, Monda J, Kamau O, Houston S, Fraser H, et al. Implementing an Open Source Electronic Health Record System in Kenyan Health Care Facilities: Case Study. JMIR Med Inform. 2018;6(2):e22.

Edgar Okoth MSM. Decentralising data-driven decision-making in Kenya: Opportunities and challenges Nutrition Exchange, 2013. Available at: Accessed on 14 April 2024.

Mboro GN. Use of routine health information for decision making among health workers at coast general hospital, Mombasa County, Kenya. Semantic Sch. 2017.

Rendell N, Lokuge K, Rosewell A, Field E. Factors That Influence Data Use to Improve Health Service Delivery in Low- and Middle-Income Countries. Glob Health Sci Pract. 2020;8(3):566-81.

WHO. Eastern Mediterranean Region: Framework for health information systems and core indicators for monitoring health situation and health system performance 2018 Cairo: WHO Regional Office for the Eastern Mediterranean, 2019. Available at: chromeextension://efaidnbmnnnibpcajpcglclefindmkaj/ Accessed on 14 April 2024.

Wekesa RN. Utilization of the health information management system by community health workers in the AMREF facility in Kibera, Nairobi County, Kenya, 2014. Available at: efaidnbmnnnibpcajpcglclefindmkaj/ Accessed on 14 April 2024.

Kawila Kyalo C, Odhiambo-Otieno GW. Transforming the Health Sector in Kenya by Adopting Integrated Health Management Information System. Int J Prof Pract. 2019;7(1):11-23.

Otieno MO, Muiruri ML, Kawila C. Organizational Determinants Of Health Information Utilization In Making Decision Among Healthcare Managers In Mombasa County, Kenya. J Heal Med Nurs. 2020;5(2):1-17.

Thomson O'Brien MA, Freemantle N, Oxman AD, Wolf F, Davis DA, Herrin J. Continuing education meetings and workshops: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2001;(2):CD003030.

Ogondi E, Otieno G, Mwanzo I, Koome G. Behavioral and Technical Factors Associated with Perceived Quality of HIV/AIDS Data Reported in Community Based Health Information System in Homa-Bay County, Kenya. Int J Sci Res Publ. 2018;8(11).

Karisa JY, Wainaina L. Balanced Scorecard Perspectives and Organizational Performance: Case of Kenyatta National Hospital, Kenya. Int J Bus Manag Entrep Innov. 2020;2(3):102-13.

Ajuwon GA. Use of the Internet for health information by physicians for patient care in a teaching hospital in Ibadan, Nigeria. Biomed Digit Libr. 2006;3:12.

Seitio-Kgokgwe O, Gauld RD, Hill PC, Barnett P. Development of the National Health Information Systems in Botswana: Pitfalls, prospects and lessons. Online J Public Health Inform. 2015;7(2):e210.

Teklegiorgis K, Tadesse K, Mirutse G, Terefe W. Level of data quality from Health Management Information Systems in a resources limited setting and its associated factors, eastern Ethiopia. SA J Inf Manag. 2016;17(1).

Jeremie N, Kaseje D, Olayo R, Akinyi C. Utilization of Community-based Health Information Systems in Decision Making and Health Action in Nyalenda, Kisumu County, Kenya. Univers J Med Sci. 2014;2(4):37-42.

Chen YC, Hsieh TC. Big Data for Digital Government: Opportunities, Challenges, and Strategies. Int J Public Adm Digit Age. 2014;1(1):1-14.

Zackery A, Zolfagharzadeh MM, Hamidi M. Policy Implications of the Concept of Technological Catch-Up for the Management of Healthcare Sector in Developing Countries. J Health Manag;25(2):144-55.

Kumar ATS, Bhattacharya SB, Amarjeet S. health system strengthening-Focussing on referrals: an analysis from India. JOJ Nurse Heal Care. 2017;2555592(24):2-4.

Chorongo DW. Determinants Of Effective Utilization Of Health Management Information For Decision Making Among Health Program Managers: A Case Of Malindi Sub County, Kilifi County, Kenya, 2016. Available at: efaidnbmnnnibpcajpcglclefindmkaj/ Accessed on 14 April 2024.

Abajebel S, Jira C, Beyene W. Utilization of health information system at district level in jimma zone oromia regional state, South west ethiopia. Ethiop J Health Sci. 2011;21(1):65-76.

Janssen M, Voort H, Wahyudi A. Factors influencing big data decision-making quality. J Bus Res. 2017;70:338-45.




How to Cite

Wangige Muhula, S., Nyamai, J. J., Odongo, A. O., & Kariuki , P. (2024). Determinants of data-driven decision-making among health providers: a case of Mombasa county, Kenya. International Journal Of Community Medicine And Public Health, 11(6), 2234–2241.



Original Research Articles