AI forces 70% cut in hospital processing time

Midcycle automation killed paperwork. 

Hospitals are increasingly using midcycle automation to streamline revenue cycle management (RCM) and boost reimbursement.

About 75% of hospitals have adopted some form of AI, from ambient scribing to robotic process automation. As automation matures, the focus is shifting from transcription quality to data interoperability and downstream readiness.

AI engines can prepopulate procedure and diagnosis codes, flag missed or unnecessary charges, and even prevent claim denials by alerting staff to eligibility or authorisation gaps.

Once focused mainly on documentation accuracy, midcycle automation now covers coding, charge capture, and claims submission.

AI-assisted tools and structured templates cut processing time by up to 70%, according to data from McKinsey, freeing medical practitioners from routine paperwork.

Advanced systems may autonomously correct errors, helping hospitals protect revenue whilst reducing administrative burden.

Experts advise modular system design, open APIs, and standardised outputs to ensure seamless future integration.

Measuring ROI should go beyond clinician time, tracking impacts on denial rates, documentation accuracy, and revenue capture.

Ambient solutions are evolving from transcription tools into foundational infrastructure for smarter RCM.

Hospitals that embrace flexible, integrated midcycle automation will improve efficiency, safeguard revenue, and position themselves for the next generation of healthcare AI innovation, according to McKinsey.