Problem definition: Business analytics (BA) in healthcare research offers numerous valuable insights that can enhance patient care and hospital performance. Consequently, there has been a rapid surge of research in this area. Academic/practical relevance: The objective of this study is to provide a data-driven summary of the extant BA in healthcare literature and a guide for future research. Methodology: Leveraging a topic modeling technique and network analysis, we provide insight into how BA topics change over time. Results: We provide an in-depth analysis of 320 articles from the University of Texas at Dallas journal list and a basic topic model and network analyses for an additional 6,515 relevant articles from PubMed published in top-tier journals across 69 medical subcategories. Our study bridges research in operations management, information systems, healthcare, and analytics by providing a definition of BA in healthcare and a road map for future research. Managerial implications: Our study provides a single source of information into operations- and analytics-related issues, such as wait times, admissions, hospital performance, etc., that scholars and administrators might use to rethink how specific processes are handled in hospitals. In addition, this work highlights how operations management research has addressed clinically important issues such as patient satisfaction, doctor ratings, readmission rates, mortality, efficiency, cost of care, and compliance with protocols of care, as all are represented in our sample. Another key contribution of our study is that we provide an interactive article analysis tool as a web application for scholars in hopes of facilitating research in this area.