Data Analytics in Healthcare: Defining the Most Common Terms

In the realm of healthcare, big data analytics are assuming an ever-more crucial role, positively impacting care quality, patient outcomes, operational efficiency, and cost control. However, successfully navigating the intricate landscape of healthcare data analytics necessitates comprehension of fundamental concepts. The American Health Information Management Association (AHIMA) defines data analytics as the utilization of quantitative and qualitative methods to scrutinize data for discerning trends and patterns. Importantly, this concept is closely intertwined with health informatics, which harnesses this data to enhance healthcare decision-making processes. Healthcare systems in the United States currently span a spectrum in their data analytics journey. Some are pioneering advanced technologies like artificial intelligence (AI) to revolutionize healthcare, while others are still grappling with the transition to electronic health records (EHRs). This divergence underscores the diverse approaches and stages of development within the healthcare data analytics landscape.