March 15, 2023 1 min read

Technologies like AI and ML have a big role to play in data-digitization, prediction-analytics and interoperability of digital healthcare data. This will facilitate better automation of tasks and decision making processes since data-driven insights are needed in order to automate processes and data-driven insights need digitized data. According to Harvard Business Review (HBR), over 70% of the healthcare data is un-structured and exists in the form of charts/notes, images, freeform text, audio/video, wearables and in proprietary formats.

A key to implementing digital transformation is data digitization and amalgamation of that data with structured and external data sets so that a 360 degree view of the patient can be achieved to provide actionable insights to Payers/Provides and the Patients. AI technologies coupled with ML algorithms in a robust data engineering framework that enables to/from integration between systems with this digitized data are needed in order to make this a reality.