Browsing by Author "Owoche, Patrick Oduor"

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A Fuzzy Ontological Model for Semantic Interoperability in Distributed Healthcare Information Systems
(International Journal of Research and Innovation in Applied Science, 2025-01-17) Okemwa, Joshua; Owoche, Patrick Oduor; Mbuguah, Samuel Mungai
The exchange of patient or care data across heterogeneous health systems is crucial in the modern healthcare ecosystem yet remains daunting. Integration and interoperability in siloed health applications require robust health information exchange (HIE) and a pragmatic ontological model to be successful. This paper details a prototype development endeavor and systematic review of literature that has pioneered the development of a robust, practical, and tested fuzzy ontological model to enhance semantic interoperability in siloed, distributed health systems. Leveraging the tenets, standards, LOINC codes, and developed model from this study will enable robust and flexible data mapping and sharing health data in an environment marred with ambiguities and uncertainties but requiring the sophistry of interoperability
Assessing Preparedness for Smart Farming and Technology Adoption among Kenyan Farmers
(International Journal of Research and Innovation in Applied Science, 2024-09-16) Gichuki, Dennis Karugu; Mbuguah, Samuel Mungai; Owoche, Patrick Oduor; Oyile, Paul Oduor
Agriculture is crucial in reducing poverty, promoting economic prosperity, and ensuring food security for the world’s growing population, which is expected to reach 9.7 billion by 2050. This sector is vital to the global economy, contributing significantly to GDP and providing jobs for a large workforce. Precision agriculture and e-commerce advances have proven beneficial, boosting crop yields and rural incomes. Sub-Saharan Africa faces similar agricultural challenges as it anticipates a population of 2.1 billion by 2050. Although the region has made strides in expanding farmland and labour, improvements in crop yields have been limited. The digital revolution offers new opportunities to tackle issues such as undernutrition by improving access to information and technology. In Kenya, with a population projected to reach 95 million by 2050, expanding food production is a pressing challenge. Significant hurdles include declining soil fertility, inadequate water management, and a lack of technical support. While technologies like Wireless Sensor Networks (WSNs) and Machine Learning (ML) have the potential to enhance agricultural productivity, their adoption is constrained by infrastructure issues, high costs, and a shortage of technical expertise. Addressing these barriers and improving farmer education is essential to fully realising these technologies' benefits.
Assessing the role of electronic health records standards in advancing semantic interoperability in distributed health systems in Kenya
(Global Journal of Engineering and Technology Advances, 2025-06-07) Okemwa, Joshua; Owoche, Patrick Oduor; Mbuguah, Samuel Mungai
Achieving semantic interoperability in distributed healthcare systems is a global challenge, especially in low-resource settings such as Kenya. Inconsistent implementation of electronic health record (EHR) standards hinders semantic interoperability by limiting the ability of distributed healthcare systems to exchange and interpret data with shared, unambiguous meaning. This study evaluates the influence of EHR standards on semantic interoperability in distributed health systems in Kenya. A mixed-method approach using descriptive and correlational research design was adopted, targeting four Level 5 public hospitals with 301 sampled respondents including system developers, health practitioners, and administrators. Statistical analyses confirmed a very weak but statistically significant correlation between EHR standards and semantic interoperability (Spearman’s ρ = 0.007, p = 0.04, N = 268). Additionally, the Kruskal-Walli’s test revealed significant differences in semantic interoperability across low, medium, and high EHR adoption groups (HStatistic = 6.52, p = 0.038), with high adopters demonstrating the highest mean rank (148.92). However, mediation analysis indicated that system usability does not significantly mediate the relationship between EHR standards and semantic interoperability (Indirect effect = -0.0004, 95% CI [-0.0125, 0.0097]). Findings highlight that EHR standards alone have limited impact, and greater interoperability gains depend on integrated approaches combining standards with usability, governance, and technical alignment.
E-learning Transforming Economies
(International Journal of Trend in Research and Development, 2016-12-28) Barasa, Peter Wawire; Owoche, Patrick Oduor; Nambiro Alice Wechuli,
as E-learning technology has quickly evolved into more sophisticated forms, it is opening the options for educators and business professionals to expand learning opportunities and transform economies globally. The ability to transform economies from low income, to more vibrant growing economies which can generate employment and growing incomes to citizens generally, has been described as economic development. It is recognized that „Human Capital,‟ a term attributed to economist Theodore Schultz, is a reflection on the human capacities. Schultz believed human capital was like any form of capital. It could be invested in through education, training and enhanced benefits that would lead to an improvement on the quality and level of production. In this paper the authors make a case of how a nation‟s education system that is E-learning relates to its economic performance
Evaluating the impact of security techniques on semantic interoperability in Kenya’s Distributed Health Information Systems
(World Journal of Advanced Engineering Technology and Sciences, 2025-05-29) Okemwa, Joshua; Owoche, Patrick Oduor; Mungai, Samuel Mbuguah
The rise of distributed health information systems in Kenya has brought significant opportunities for enhancing clinical efficiency and patient outcomes through electronic data exchange. However, semantic interoperability, the ability of systems to exchange data with shared, unambiguous meaning, remains severely constrained by inconsistent adoption of security techniques such as access control and encryption. Weak security measures not only compromise data integrity and confidentiality but also hinder healthcare professionals' trust and willingness to engage in interoperable data exchange. This study aimed to evaluate the impact of security techniques on semantic interoperability in Kenya’s distributed healthcare systems. The central research question guiding this inquiry was: What is the impact of security techniques on semantic interoperability in healthcare data exchange? The target population consisted of healthcare professionals, system administrators, developers, and records officers in four Level 5 hospitals across Kenya: Kisii, Nyeri, Nakuru, and Coast General Teaching and Referral Hospital. A sample of 301 respondents was determined using Yamane’s formula, with participants selected through purposive and stratified random sampling techniques. Data collection employed structured questionnaires, complemented by interviews and focus group discussions for triangulation. Descriptive statistics (frequencies, percentages, means) were used to summarize respondent characteristics and perceptions. Inferential analysis included Spearman’s correlation, Mann-Whitney U test, and bootstrapped mediation analysis, conducted using SPSS to explore the relationship between security techniques and semantic interoperability, as well as the mediating role of system usability. Ethical approval was obtained from the National Commission for Science, Technology and Innovation (NACOSTI) and respective hospital boards. Informed consent was secured from all participants, and data confidentiality was strictly maintained. Findings revealed a significant but weak positive correlation between security techniques and semantic interoperability (ρ = .053, p = .002). Descriptively, institutions that reported higher levels of access control and encryption practices showed increased semantic data exchange effectiveness. The Mann-Whitney U test confirmed statistically significant differences in semantic interoperability scores between institutions with robust and weak security practices (U = 7425, p = .005). Moreover, system usability was found to significantly mediate the relationship between security techniques and semantic interoperability (β = .400, p < .001), underscoring the importance of user-centered design in leveraging security for interoperability gains. The study concludes that while security techniques positively influence semantic interoperability, their impact is contingent upon the usability of health information systems. It recommends the national enforcement of security protocols such as role-based access control (RBAC) and encryption standards, alongside targeted training programs to enhance system usability among healthcare staff. Strengthening both technical safeguards and human-centered design will be critical in advancing trustworthy and interoperable healthcare data exchange in Kenya’s distributed environments.
Evaluating total cost of ownership for university enterprise resource planning: case of Maseno university
(2015) Owoche, Patrick Oduor; Gregory, Wanyembi; Juma, Kilwake Humphrey
Higher learning institutions (HEI) are investing in IT to attain operational excellence. Organizations looking to reduce technology costs typically look for ways to reduce the Total Cost of Ownership (TCO). TCO captures all direct and indirect costs related to deploying a particular system. Understanding life-cycle costs provides opportunity to save scarce resources, improve IT and increase productivity. The study sought to analyze the TCO of university ERP system. The TCO analysis was based on Gartner’s TCO model, the Distributed Computing Chart of Account as the theoretical framework. Modified Gartner TCO model was used to determine the total cost of owning Maseno University ERP system. The aim of the study was to create awareness on life-cycle costs of ERP solutions. The results obtained indicate that operations and maintenance account for 51%, end-user usage 23% while technology acquisition costs accounted for 16 %, implementation costs with 7% and the least cost was taken by procurements costs with 3%. Case study was used in gathering both qualitative and quantitative data from Maseno University. Interviews, document analysis, and questionnaires were used to gather the research data. It is hoped that the results of this study will help HEIs improve management of their ERP systems.
Global Information Technology Infrastructure in Addressing the Problem of Environmental Degradation in Kenya
(International Journal of Information Technology Convergence and Services, 2019-02-27) Owoche, Patrick Oduor; Wabwoba, Franklin; Wechuli, Alice Nambiro
Information Technology (IT) infrastructure and related research communities can help tackle environmental challenges in developing countries through environmentally sustainable models of economic development. The paper sought to examine the status of current and emerging environmentally friendly technologies, equipment and applications in supporting programs that play a role in addressing environment degradation in Kenya. It also sought to underscore the role of IT in environmentally sustainable consumption. The paper examines what constitutes environment degradation and explores the negative effects of IT infrastructure on the environment. The consequences of E-waste on environment are discussed followed by green IT as part of the solution to environment degradation as a result of adoption of IT. The papers also discuss the available IT infrastructure that can be used to combat the challenges of environment degradation. The paper ends with possible IT infrastructure measures that can be used to mitigate environment degradation.
Performance Evaluation of Machine Learning Algorithms in Smart Agriculture
(International Journal of Advanced Research in Computer and Communication Engineering, 2024-08-26) Gichuki, Dennis Karugu; Owoche, Patrick Oduor; Mbuguah, Samuel Mungai
This study explores the integration of Wireless Sensor Networks (WSN) and Machine Learning (ML) in smart farming to address critical agricultural challenges. By leveraging real-time data collection and advanced analytical tools, the research demonstrates the potential of ML algorithms—Decision Trees, Naive Bayes, Support Vector Machines (SVM), Logistic Regression, and Random Forests—in enhancing crop management, including yield prediction, soil quality assessment, and pest and disease detection. The study finds that Naive Bayes achieves the highest accuracy and balanced precision-recall metrics, while ensemble methods like Random Forests effectively reduce overfitting and improve prediction accuracy. Despite the promising results, the research identifies challenges such as data accessibility, model integration, and user interface design that must be addressed to fully realize the potential of smart farming technologies. Overall, the findings provide valuable insights into optimizing resource utilization, reducing crop losses, and promoting sustainable farming practices, thereby supporting global food security and economic stability.