Leveraging Data Analytics for Better Patient Care and Operational Effectiveness in Indian Hospitals

Abstract

India's healthcare sector is poised for a growth trajectory, and it is expected to reach approximately $193 billion in 2032, with a CAGR of about 8%, fuelled by a growing population and government schemes like Ayushman Bharat; however, the industry demands immediate attention owing to an enormous and heterogeneous population. This study aims to explore how healthcare professionals, administrators, and IT specialists perceive the consequences of data analytics for decision-making, patient care, and hospital operations by examining trust/charitable, private, and government hospitals through a survey-based approach. Using a sample of 380 respondents and a well-developed questionnaire, the research employs the Technology Acceptance Model (TAM) to evaluate the working competence of hospitals through patient care activities. Statistical techniques including correlation, regression, and Analysis of variance (ANOVA) and Structural Equation Modeling (SEM) using AMOS and the statistical package SPSS were used to find the association among the constructed variables. The results show that all the hypotheses were validated and that adoption is significantly influenced by perceived usefulness (β = 0.067, p < 0.001) and usability/ease of use (β = 0.398, p < 0.001). Furthermore, strong paths between Perceived Ease of Use (PEOU) and Usefulness (β = 0.402, p < 0.001), and Behavioural Intention (BI) and Actual System Use (ASU) (β = 0.416, p < 0.001) are also confirmed by the analysis. The empirical analysis further shows that the biggest obstacles are data integration (74%), training of employees (54%), and data privacy issues (44%). The research concludes that data analytics is an important tool for hospitals to improve their operational performance, but insists on the need for technological investment and strategic planning to overcome barriers to implementing and promoting long-term efficiency in Indian hospitals.