SU+ Digital Repository

SU+ is an online repository for the preservation and promotion of assorted digital content at Strathmore University

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Conferences / Workshops / Seminars + 474
Documents and Proceedings of Conferences, Seminars, Workshops (and more) held at Strathmore University
Digital Archives 178
Assorted collections of resources covering various subject themes contributed by Faculty and Library Staff
Reports / Policies + 10
Public reports and policy documents
Research / Researchers / Publications 4669
Researcher Profiles / Conference presentations / Published research articles / Faculty and Corporate research outputs
Strathmore Heritage Collection 41
A digital chronicle of the History of the University presented through a mix of pictures, videos and digitized publications

Recent Submissions

Influence of health management information systems on decision-making in a level 5 public hospital in Tharaka Nithi County, Kenya
(Strathmore University, 2026) Gichohi, Grace W.
The effective utilization of Health Management Information Systems (HMIS) plays a pivotal role in evidence-based decision-making in healthcare. In Kenya, the rollout of digital platforms such as Afya Kenya, under the Digital Health Act 2023, underscores the government’s commitment to improving data-driven planning and service delivery. However, limited evidence exists on how healthcare workers, particularly in public facilities, use HMIS for operational and strategic decisions. The study examined the influence of HMIS on decision-making among healthcare workers at Chuka County Referral Hospital, a Level 5 public hospital in Tharaka Nithi County, Kenya. The objectives were to evaluate the technical, behavioral, organizational, and environmental factors influencing the use of HMIS data for decision-making. It was anchored on the PRISM Framework and Theory of planned behavior, which together provided a structured approach to understanding the enablers of data-driven decision-making in healthcare. A descriptive cross-sectional design was employed. The study adopted a census method, targeting all 250 departmental heads and clinical staff involved in data management and decision-making within the facility. Data were collected using semi-structured questionnaires and analyzed using descriptive statistics, Pearson correlation, and multiple linear regression. Correlation results showed, organizational factors had the strongest correlation (r = 0.682), followed by behavioral (r = 0.634), technical (r = 0.501), and environmental (r = 0.372) factors. However, regression analysis revealed a more nuanced picture by identifying which factors significantly predict actual HMIS data use. It showed that organizational factors were most statistically significant predictors (β = 0.476, p < 0.05) in strategic and (β = 0.521, p < 0.05) in operational decision making. The study concluded that while technical infrastructure and staff attitudes are important, organizational leadership, policies, and governance structures are the most critical drivers of effective HMIS data utilization. Recommendations made include strengthening internal leadership and accountability mechanisms, enhancing system interoperability, providing regular staff training, and developing policy frameworks that decentralize data-driven decision-making. These findings offer practical guidance for healthcare managers and policymakers seeking to optimize HMIS adoption for improved healthcare delivery.
Factors influencing adoption of electronic medical records amongst private dental clinics in Nairobi and Mombasa Counties, Kenya
(Strathmore University, 2026) Aliyan, Khadija K.
Despite the recognized benefits of Electronic Medical Records (EMRs) in improving healthcare efficiency, data management, and continuity of patient care, adoption within Kenya’s private dental sector remains inconsistent and insufficiently understood. This study investigated the factors influencing EMR adoption among private dental clinics in Nairobi and Mombasa Counties, Kenya. Guided by the Diffusion of Innovations (DOI) theory and the Technology Acceptance Model (TAM), the study examined the association between system-related, organizational, and policy/environmental factors and EMR adoption and integration within routine dental practice. The study employed a quantitative analytical cross-sectional design among registered private dental clinics in Nairobi and Mombasa Counties. Data were collected using a structured online questionnaire administered to respondents involved in EMR implementation and management. Data were collected using a structured online questionnaire and analyzed using chi-square tests, Pearson correlation, multiple regression, and ordered logistic regression analysis. The findings demonstrated significant associations between EMR adoption and clinic location (χ² = 34.107, p < 0.001), clinic size (χ² = 44.402, p < 0.001), and clinic ownership (χ² = 22.337, p = 0.001). Correlation analysis revealed that organizational factors had the strongest positive relationship with EMR adoption (r = 0.385, p < 0.01), followed by system-related factors (r = 0.251, p < 0.01), while policy and environmental factors demonstrated no statistically significant relationship with EMR adoption (r = -0.054, p > 0.05). Multiple regression analysis identified organizational readiness as the only statistically significant predictor of EMR adoption (β = 0.278, p < 0.001). Similarly, ordered logistic regression analysis showed that organizational readiness significantly increased the likelihood of higher levels of EMR adoption (β = 1.411, p < 0.001), while demographic and policy/environmental variables remained statistically insignificant. Qualitative responses suggested that EMR implementation was perceived to be more integrated in Nairobi than in Mombasa, although the contextual factors underlying these differences were beyond the scope of the present study. The study concludes that organizational readiness—including leadership support, workflow integration, resource availability, technical support, and staff training—was more strongly associated with EMR adoption than system-related or policy/environmental factors. The study recommends that private dental clinics in Kenya to strengthen organizational readiness through leadership engagement, continuous staff training, workflow integration, and structured technical support to promote sustainable EMR adoption.
The Determinants of mental health financing in Kenya: towards a stakeholder-informed framework for sustainable financing
(Strathmore University, 2026) Mutua, Karen
Mental health services in Kenya face a severe funding crisis. Despite contributing approximately 15% of the national disease burden, the sector receives less than 1% of the health budget, resulting in inadequate services, medication shortages, and a treatment gap affecting three-quarters of those who need care. This chronic underfunding persists despite the progressive frameworks established by the Kenya Mental Health Policy (2015–2030) and the Mental Health (Amendment) Act, 2022. While existing research has documented the burden of mental illness and service availability gaps, the underlying determinants of fiscal neglect—particularly institutional stigma, political economy dynamics, and the internal prioritization logics of financing institutions—remain poorly understood. This study examined the determinants of mental health underfunding by exploring the perspectives of 32 key informants across the National Treasury, Ministry of Health, Social Health Insurance Fund, county health departments, service providers, civil society organisations, and community representatives. A qualitative case study design was employed, with data collected through semi-structured interviews and analyzed using reflexive thematic analysis. Four themes emerged. Institutional and governance barriers encompassed fragmented county governance post-devolution, mental health's marginal positioning within the Ministry of Health, inter-agency coordination failures between Treasury, MoH, SHIF, and county governments, and capacity constraints at all levels. Stigma and perceptions as a fiscal determinant included the perception of mental illness as less medically legitimate, productivity biases discounting treatment returns, and selective evidence dismissal — with 50% of participants questioning the KES 62 billion economic cost estimate despite its methodological equivalence with accepted figures for other conditions. Political economy and financing mechanism feasibility identified absent parliamentary champions, fragmented civil society advocacy, donor crowding-out, and rated SHIF benefit package expansion and conditional grants as the most feasible reform pathways. The stakeholder verdict converged across all participant groups on institutional stigma, political invisibility, and fiscal unprotection as three interlocking mechanisms sustaining the less-than-1% allocation. The study extended Modified Labeling Theory to fiscal policy decision-making, demonstrated the value of stakeholder-centred qualitative methods in health financing research, and generated evidence-based recommendations toward sustainable mental health financing and Universal Health Coverage in Kenya. Keywords: mental health financing, health policy, stakeholder perspectives, institutional stigma, sustainable financing, Kenya, Universal Health Coverage
Organizational support for mitigating work-related stress among emergency department staff: a cross-sectional study of level 5 hospitals in Nairobi County, Kenya
(Strathmore University, 2026) Kaseve, Mary Goretti Mukai
The Work-related stress among emergency department staff is a global concern, yet little empirical evidence exists on how organizational support and staff perceptions shape stress outcomes in African emergency care settings. Prior studies in Kenya have focused mainly on clinicians, overlooking non-clinical cadres, and have rarely compared hospital ownership models. Moreover, the mediating role of staff perceptions, central to Organizational Support Theory, has not been systematically tested in resource-constrained emergency departments. This study addressed these gaps by investigating work-related stress and the adequacy of organizational support among clinical and non-clinical staff in three Level 5 hospitals in Nairobi County (public, private, and faith-based). Using a cross-sectional convergent parallel mixed-methods design, quantitative data from 133 respondents were analysed in IBM SPSS, while qualitative data from open-ended responses and nine key informant interviews were thematically analysed in NVivo 14. Findings showed that 90.2% of staff experienced moderate to high stress (mean = 4.75/7.00), driven by heavy workload (57.9%), staffing shortages (44.4%), and resource inadequacy. Organizational support significantly predicted stress outcomes (β = 0.550, R² = 0.349, p < .001), yet emotional support and resource adequacy scored below the midpoint, and 60.2% of staff rated existing support as ineffective. Staff perceptions partially mediated the support–stress relationship, transmitting nearly half (49.6%) of the total effect, with management responsiveness and support effectiveness rated lowest. Counselling was underutilized due to confidentiality concerns, while informal peer networks emerged as the primary coping buffer. The study contributes novel evidence by extending Organizational Support and Job Demands–Resources models into African emergency care, incorporating non-clinical cadres and hospital ownership comparisons, and empirically confirming the mediating role of staff perceptions. Practically, the findings underscore that occupational stress in Nairobi’s emergency departments is structurally embedded and requires systemic interventions. Recommendations for healthcare administrators include annual staffing needs assessments, externally contracted employee assistance programs accessible across shifts, and equitable recognition frameworks to strengthen workforce resilience and retention. By integrating clinical and non-clinical cadres across hospital ownership models, the study advances methodological inclusivity and provides context-specific evidence to guide organisational reforms in African emergency care.
Examining the effect of laboratory turnaround time on hospital performance: a case study of Nakasero Hospital in Uganda
(Strathmore University, 2026) Bakari, Asiah Odongo
Laboratory turnaround time (TAT) is a critical indicator of healthcare service delivery because it influences the timeliness of diagnosis, treatment initiation, and overall hospital performance. In low- and middle-income countries (LMICs), delays in laboratory processes continue to pose significant challenges to healthcare systems by contributing to prolonged hospital stays, reduced service efficiency, increased costs of care, and suboptimal patient outcomes. Despite the importance of laboratory services, limited empirical evidence exists on the effect of laboratory turnaround time on hospital performance within private tertiary healthcare facilities in Uganda. This study examined the effect of laboratory turnaround time on clinical efficiency, service quality and financial performance at Nakasero Hospital in Kampala, Uganda. The study was guided by Lean Management Theory and the Theory of Constraints and adopted a Sequential Explanatory Mixed-Methods Research Design. Quantitative data were collected through a retrospective review of 217 eligible patient records extracted from the Laboratory Information System (LIS), Electronic Medical Records (EMR) and hospital billing records. Qualitative and perceptual data were collected through a survey of 60 healthcare workers comprising clinicians, nurses and laboratory personnel. Quantitative data were analyzed using descriptive statistics, Pearson correlation analysis, multiple linear regression and analysis of variance, while qualitative data were analyzed thematically. The mean total laboratory turnaround time was 198.4 ± 112.5 minutes. The analytical phase accounted for the largest proportion of intra-laboratory processing time (53.0%). Healthcare workers identified equipment functionality (M=2.85±0.88) and staffing adequacy (M=2.90±0.82) as key constraints. Multiple regression analysis showed that equipment functionality (β=-0.412, p<0.001) and staffing adequacy (β=-0.385, p=0.002) were significant predictors of TAT, explaining 54.2% of its variance (Adjusted R²=0.542). Total TAT was positively associated with length of stay (r=0.48, p<0.001) and increased cost of care (β=0.406, p<0.001), while negatively affecting adherence to clinical protocols (β=-0.584, p<0.001). Laboratory TAT significantly influences clinical efficiency, service quality, and financial performance. The study recommends investment in laboratory automation, strengthened equipment maintenance, improved staffing levels, enhanced laboratory information system integration and implementation of lean workflow strategies to reduce bottlenecks and improve hospital performance.