Factors Influencing Utilization of Health Data for Decision Making by Community Members in Nyando Sub-County, Kenya

Henry Kilonzo, Dr. Doreen Othero and Dr. Benard Guyah
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Henry Kilonzo: Department of Public Health, Maseno University
Dr. Doreen Othero: Department of Public Health, Maseno University
Dr. Benard Guyah: Department of Biomedical Sciences and Technology, Maseno University

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 15, 1443-1458

Abstract: Utilization of health data is key because it enables individuals and communities to make decisions on their health seeking behaviour. However, studies show low utilization of health data for this purpose. In Kenya, majority of health programs provide feedback on health data to communities through conventional methods such as health talks in health facilities, use of mass media, posters and billboards. Despite these, less than 38% of health data is used for decision making. This can be attributed to the ineffective methods of providing feedback to communities. This study therefore investigated the factors influencing utilization of health data for decision making among community members. It was a longitudinal interventional (pre-post) study for 12 months. 440 participants were sampled using Yamane’s formula. Quantitative data was collected using semi-structured questionnaires while qualitative data was collected through Focus Group Discussions and Key Informants Interviews. Quantitative data was analyzed using SPSS version 25 and R. Qualitative data was analyzed using the NVivo application. Utilization of health data for decision making at baseline showed that use of prevention of malaria data was at 187 (42.5%), TB prevention at 188 (42.7%), HIV/AIDS prevention 210 (47.8%), ANC 123 (28%), Deworming 146 (33.2%), Child Immunization 156 (35.5%) and hygiene and sanitation was at 117 (26.6%). Findings from the qualitative survey resonated with these results. The main factors that influenced utilization of health data for decision making were; Education Level, for HIV data use (P=0.01, OR=2.5); Age, for malaria data use (p=0.07, OR=2.05); Education Level, for TB management data use (P=0.00, OR=2.3); Religion, for ANC data use (P=0.02, OR 2.2); and Gender, for child immunization data use (p=0.03, OR=1.7). The key factors found to influence utilization of health data included: Age, education level, religion and number of children per household.

Date: 2025
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