Abstract
Despite significant investments in health programs in Nairobi County, Kenya, the effectiveness of monitoring and evaluation (M&E) practices remains a critical challenge, often hindered by outdated methods and inadequate technological support. This study investigated the impact of technological tools on the effectiveness of M&E practices in these health programs. As health programs increasingly rely on accurate and timely data to guide decision-making and improve outcomes, the integration of advanced technological tools becomes essential. This research focused on two key technological areas: data collection tools and data analysis tools and how they influence the effectiveness of M&E processes. A descriptive research design was adopted for the study, targeting a population of 60 management-level employees working across various health programs. Given the relatively small size of the population, a census sampling approach was used, ensuring that all eligible participants were included in the study. Data was collected using a structured questionnaire, which combined both closed-ended and open-ended questions to gather comprehensive insights from respondents. The collected data was analyzed using descriptive and inferential statistical techniques, including regression analysis, to explore the relationships between the use of technological tools and the effectiveness of M&E practices. The findings provide valuable insights for policymakers, health program managers, and technology developers, highlighting the importance of investing in technology and capacity building to maximize the effectiveness of M&E practices in resource-constrained settings. This research contribute to the broader understanding of how technology can be leveraged to improve public health outcomes. The findings revealed that technological components had a statistically significant and positive relationship with M&E effectiveness. Among them, data analysis tools emerged as the strongest predictor, followed by data collection tools. The study concludes that integrating digital tools at all stages of the M&E cycle enhances data accuracy, timeliness, decision-making, and stakeholder communication. The study recommends strategic investments in analytical capacity, interoperable data systems, digital literacy training, and collaborative platforms to strengthen M&E performance in health programs. These findings provide practical guidance for policymakers, development partners, and program managers aiming to enhance evidence-based decision-making through technology-enabled M&E systems.
Key Words: Tech Solutions, Monitoring and Evaluation, Health Programs, M&E practices, data collection tools, data analysis tools