ABSTRACT
The rise of the intelligent health system inherently conjures visions of rich data, deep analysis, and instantaneous on-the-fly decision support or even artificial intelligence. The reality is that many health systems still struggle with multiple core information systems, lack of standardization, lack of governance, and challenges with agreed-upon sources of truth. There is no shortage of data generated by healthcare organizations but making that data actionable at the point of care is still much more of a desire than it is a reality. A recent study by the Virtusa Corporation indicates that healthcare firms typically lag about a decade behind other industries in adopting business technologies that would help with customer engagement. This is not just a technology problem, there are significant people and process issues that contribute to the lag. There is progress and certainly some health systems are seeing success, even integrating patient genetic testing to guide treatment, especially for cancer patients. The recent events associated with COVID-19 have accelerated adoption of technology and data in areas such as telemedicine and use of predictive analytics to determine levels of remote outreach to patients. This chapter will examine the current state of informatics and analytics in healthcare along with the challenges and progress being made.
