The Effect of technology adoption on healthcare quality improvement at Lamu County Referral Hospital

Abstract

The persistent challenge of inadequate healthcare quality in Kenya, particularly in underserved regions like Lamu County, necessitates urgent attention. Despite global and national advancements in health technology, public facilities such as Lamu County Referral Hospital continue to face infrastructural, operational, and technological deficiencies that hinder effective service delivery. This study aimed to assess the effect of technology adoption on healthcare quality improvement at Lamu County Referral Hospital, with a focus on four key areas: barriers to successful adoption and integration of technology, technological healthcare infrastructure, hospital management systems, and telemedicine. Guided by the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT), the study adopted a positivist philosophy and case study research design. The research was conducted at Lamu County Referral Hospital, targeting all 129 healthcare providers as the study population, using a census sampling procedure. Inclusion criteria required participants to be healthcare professionals with at least six months of work experience at the facility; non-medical staff and those unwilling to consent were excluded. Ethical considerations were strictly adhered to, including informed consent, confidentiality, and voluntary participation. Primary data were collected using a semi-structured questionnaire, pretested for clarity and reliability. The quality of the research instrument was confirmed with Cronbach’s alpha values above 0.65 and KMO statistics exceeding 0.67. Data were analysed using descriptive statistics, Pearson correlation, and multiple regression analysis. The study achieved a high response rate of approximately 98%. Most respondents were nurses, and over 60% had more than five years of work experience. Results showed that technological healthcare infrastructure had the most substantial effect on healthcare quality (β = 0.442, p < 0.05), followed by hospital management systems (β = 0.378, p < 0.05), and telemedicine (β = 0.264, p < 0.05). Conversely, barriers to technology adoption showed a weak and statistically insignificant influence (β = 0.051, p > 0.05). The study concluded that modernising healthcare infrastructure and strengthening hospital management and telemedicine systems significantly enhance healthcare quality in public hospitals, even when adoption barriers exist. It recommended prioritised investment in physical infrastructure, comprehensive digital training for healthcare staff, expansion of telemedicine access, and process automation within hospital management. The main limitations included the study’s confinement to a single facility and reliance on self-reported data. Future research should explore longitudinal impacts of technology on patient outcomes and replicate the study in diverse settings to strengthen generalisability.