Influence of Big Data Analytics Adoption on Healthcare Service Quality in Kenya
DOI:
https://doi.org/10.47672/ejt.2068Keywords:
Big Data Analytics, Healthcare, Service QualityAbstract
Purpose: The aim of the study was to assess the influence of big data analytics adoption on healthcare service quality in Kenya.
Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
Findings: The adoption of big data analytics in healthcare has demonstrated significant impacts on enhancing service quality across various dimensions. Study findings suggest that healthcare organizations leveraging big data analytics experience improvements in clinical outcomes, patient satisfaction, and operational efficiency. By analyzing vast amounts of data, including electronic health records, medical images, and patient feedback, healthcare providers can identify patterns, trends, and predictive insights that enable more personalized and effective care delivery. Additionally, big data analytics facilitates proactive interventions, early disease detection, and better resource allocation, leading to optimized healthcare services and reduced costs. Moreover, the integration of advanced analytics tools enables healthcare professionals to make data-driven decisions, enhance care coordination, and improve overall patient experiences.
Implications to Theory, Practice and Policy: Technology acceptance model, resource-based view and innovation diffusion theory may be used to anchor future studies on assessing the influence of big data analytics adoption on healthcare service quality in Kenya. Healthcare organizations should prioritize the development of data-driven cultures that promote the effective utilization of big data analytics to drive decision-making and improve service quality. Policymakers should collaborate with healthcare stakeholders to develop robust regulatory frameworks that govern the ethical collection, storage, sharing, and analysis of healthcare data.
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