Disruptive Technology and Operational Efficiency of Private Hospitals in Kenya

Abstract

Purpose: The primary objective of this study was to examine the effect of disruptive technologies—specifically telemedicine and artificial intelligence (AI)—on the operational efficiency of private hospitals in Kenya.

Material/methods: The study was grounded in the Unified Theory of Acceptance and Use of Technology and the Technology Acceptance Model. An explanatory research design was employed. The target population comprised 446 Level 4 private health facilities across Kenya. Using simple random sampling, a sample of 211 hospitals was selected, and respondents were drawn from IT and Operations Department Heads. Data was collected through structured questionnaires. Content validity and Cronbach’s Alpha were used to assess the instrument's validity and reliability. Data analysis involved descriptive statistics (means, standard deviations, frequencies, and percentages) and inferential statistics (Pearson correlation and multiple regression) to test the study hypotheses.

Findings: The results indicated that both telemedicine and artificial intelligence have a statistically significant positive effect on operational efficiency in private hospitals. Specifically, these technologies improve service delivery, enhance resource utilization, and strengthen patient care processes.

Conclusion: The study concludes that disruptive technologies play a vital role in optimizing hospital operations. However, the realization of their full benefits is contingent on addressing challenges related to cost, accessibility, and data security.

Value: The study underscores the need for private hospitals to invest in supportive infrastructure, capacity building, and regulatory frameworks to facilitate effective technology adoption. Emphasis on cybersecurity and equitable access strategies is essential to ensure sustainable integration of telemedicine and AI into hospital operations.