THE IMPACT OF DATA ANALYTICS ADOPTION AND INFLUENCING FACTORS ON HEALTHCARE OUTCOMES

Abstract

Background: Data analytics is increasingly used in healthcare to improve patient outcomes and reduce costs, yet its effectiveness is influenced by multiple factors.
Objective: This study explores the impact of data analytics adoption on healthcare outcomes and identifies key factors influencing its effectiveness.
Methods: A survey of 100 healthcare professionals was conducted to assess the relationship between data analytics adoption, frequency of use, data quality, and healthcare outcomes. Regression analysis was used to examine these relationships.
Results: A weak positive correlation was found between data analytics adoption and healthcare outcomes (R² = 0.019). Frequent implementation and high data quality significantly improved outcomes. Organizational factors, such as skilled personnel and infrastructure, also played a critical role.
Conclusion: Effective data analytics in healthcare requires more than just adoption; frequent use, high data quality, and strong organizational support are essential for achieving optimal outcomes.