Data has become the backbone of informed decision-making across industries, including healthcare. The adoption of Electronic Health Records (EHR) has amplified the importance of data, making data visualization an indispensable tool for professionals [1]. Effectively extracting and visualizing data into valuable insights can produce remarkable outcomes in the decision-making process involved in the healthcare domain [2]. As the healthcare industry uses the ever-increasing volume and complexity of medical data, data visualization tools have emerged as promising solutions for enhancing decision-making processes. According to a survey conducted by HealthIT.gov 2017, 94% of healthcare organizations reported using electronic clinical data from their EHR to support decision-making processes. The same survey, however, also indicated that only 31% of respondents believed that their organizations were highly effective in leveraging visualization tools for decision support [3]. This discrepancy highlights a gap between the widespread implementation of data visualization tools and the perceived effectiveness of their adoption in healthcare decision-making. Historically, decision-making in the clinical aspect of healthcare relied on manual analysis of patient records and limited datasets [3]. With the digitization of health records and the exponential growth of data in the health sector, the need for advanced tools to extract meaningful patterns is evident. The use of electronic health records (EHRs) has changed how we gather large datasets, with the potential to revolutionize decision-making processes in the healthcare domain. This research aims to investigate the influence of data visualization tools on decision-making processes within the healthcare domain, focusing on the users' perspective. The primary line of inquiry will examine how users and healthcare professionals, including clinicians, administrators, and analysts, perceive and interact with data visualization tools in their decision-making processes. The research will explore the features and elements that users find most valuable or challenging, seeking insights into how integrating data visualization tools can be improved to enhance decision-making.