Traditional charge capture in healthcare is often a manual, error-prone process. Clinicians and administrative staff must meticulously record the services provided, the relevant codes, and the associated charges, frequently navigating complex coding systems. This reliance on human input leads to inaccuracies, missed billable services, and delays in the revenue cycle. The sheer volume of patient encounters, combined with the ongoing evolution of healthcare regulations, creates … Continue reading Automating Charge Capture: How AI and Machine Learning are Transforming Billing Workflows