Impact of AI and big data analytics on healthcare outcomes: An empirical study in Jordanian healthcare institutions

Abstract

Artificial intelligence (AI) and big data analytics are transforming healthcare globally and in Jordan. This study investigates the effects of AI and big data analytics on healthcare outcomes in Jordanian healthcare institutions. A comprehensive model is proposed to understand the antecedents of healthcare outcomes, including the impact of perceived ease of use, perceived usefulness, and organizational capabilities. Data were collected from 400 structured questionnaires, with a final sample size of 288 respondents, and analyzed using partial least squares structural equation modeling. The findings reveal that AI technologies significantly improve diagnostic accuracy and treatment planning, while big data analytics enhances operational efficiency and patient care. However, the comparative influence of AI on different healthcare processes was less significant. Additionally, robust organizational capabilities effectively enhanced the adoption and impact of AI and big data analytics. The study highlights the mediating roles of perceived ease of use and usefulness in the relationship between technology adoption and healthcare outcomes. Understanding the interplay between AI, big data analytics, and healthcare delivery is crucial for policymakers, healthcare administrators, and technology developers to develop effective strategies that improve patient care and operational efficiency. This study recommends investing in user-friendly AI and big data analytics tools, enhancing organizational capabilities, and providing comprehensive training for healthcare professionals. Future research should extend this study to different cultural contexts to validate the findings and contribute further to the literature on AI and healthcare.

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