Utilization of data visualization tools to inform decision-making among health managers in selected counties in Kenya
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Date
2025-05
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Kenyatta University
Abstract
This study investigated the factors influencing the utilization of data visualization (DV) tools among county and sub-county health managers in selected counties in Kenya. The research was motivated by the persistent underuse of health information despite substantial investments in data collection across various programs. Four specific objectives guided the inquiry: determining the effects of (i) individual characteristics, (ii) technological factors, (iii) organizational factors, and (iv) behavioural factors on the utilization of DV tools for decision-making. Additionally, the study assessed how these factors collectively impact effective evidence-based decisions in healthcare management. A mixed-methods, longitudinal case study design was adopted, combining quantitative (structured questionnaires) and qualitative (key informant interviews) approaches. Eight counties, Machakos, Isiolo, Nyeri, Kisumu, Makueni, Mombasa, Laikipia, and Garissa, were purposively selected to reflect diverse healthcare settings and varying degrees of Universal Health Coverage implementation. The target population comprised 294 county and subcounty health managers, with 160 chosen via purposive sampling. A total of 149 respondents participated, yielding a 93% response rate. Data collection included structured questionnaires focused on demographics, data utilization practices, and training; key informant interviews provided more profound insights into organizational culture, leadership support, and policy frameworks. Quantitative data were analysed using descriptive statistics, correlation analysis, and multiple regression with SPSS (v.26). Qualitative data underwent thematic and content analysis, capturing nuanced perspectives on facilitators and barriers to DV adoption. Findings indicated that all four categories of factors significantly influence DV-tool utilization. Correlation coefficients showed strong positive associations between use of DV tools and (a) individual characteristics (r=0.504, p<0.05), (b) technological factors (r=0.784, p<0.001), (c) organizational factors (r=0.776, p<0.001), and (d) behavioural factors (r=0.404, p<0.001). A combined R² value of 0.823 suggested that over 82% of the variation in DV-tool utilization could be attributed to these four dimensions, underscoring their collective influence on data-driven decision-making. The final regression model highlighted training, infrastructure, supportive management, and positive staff attitudes as key predictors. The study recommends that strengthening data visualization competencies among health managers, improving technology and infrastructure, and fostering an organizational culture that values evidence-based decision-making are critical for enhancing health service delivery. The study recommends targeted training on advanced analytics, continuous mentorship, and clear governance frameworks to sustain DV-tool usage, thereby optimizing healthcare outcomes and supporting Kenya’s progress toward Universal Health Coverage
Description
A thesis submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy in Health Information Management in the School of Health Sciences Of Kenyatta University,
May 2025
Supervisors:
Dr. Joyce Kirui
Dr. Peter Kithuka