ABSTRACT
This chapter provides an understanding of big data, AI, and interoperability in the context of healthcare. Big data analytics can analyze and predict patient diagnosis, treatment, medication safety, and patient characteristics. They can also improve provider productivity by converting speech to text, recognizing patterns in radiological images, and extracting relevant clinical data from unstructured data sets such as discharge summary and progress note. Additionally, AI/ML systems have gradually gained acceptance due to availability of big data, cloud computing, and sophisticated computational AI tools to generate ML algorithms. Interoperability can support value-based care and Population Health Management to manage high-risk or at-risk patient populations. Several health information exchanges have been formed to support Accountable Care Organizations to manage care costs, improve patient access to their healthcare, and increase patient satisfaction. The chapter concludes by assessing the relationship between these technologies and digital transformation of Healthcare Organizations.
