Abstract: Techniques for medical coding include applying a natural language understanding (NLU) engine to a free-form text documenting a clinical patient encounter, to derive a first set of one or more medical billing codes for the clinical patient encounter and a link between each code in the first set and a corresponding portion of the free-form text. The first set of codes may be compared to a second set of one or more medical billing codes approved by one or more human users for the patient encounter, to identify at least one code in the first set that overlaps with at least one code in the second set. The code in the second set approved by the one or more human users may be retained instead of the overlapping code in the first set derived by the NLU engine.

Abstract: In a system with a display and an input device, a graphical user interface (GUI) may be presented via the display. A natural language understanding engine may be applied to a free-form text documenting a clinical patient encounter, to automatically derive one or more engine-suggested medical billing codes, which may be presented in the GUI. User input may be accepted to approve at least one of the engine-suggested codes and/or to enter one or more user-added codes in the GUI, resulting in a set of user-approved codes. The set of user-approved codes may be automatically correlated to a diagnosis related group (DRG) for the patient encounter, which may be displayed. In response to user input changing the set of user-approved codes by approving or removing approval of an engine-suggested code in the GUI, the DRG may be automatically updated, and the updated DRG for the patient encounter may be displayed.

Abstract: In a system with a display and an input device, a graphical user interface (GUI) may be presented via the display. A natural language understanding engine may be applied to a free-form text documenting a clinical patient encounter, to automatically derive one or more engine-suggested medical billing codes, which may be presented in the GUI. User input may be accepted to modify the engine-suggested codes in the GUI, resulting in an unfinalized set of user-approved codes for the patient encounter. The natural language understanding engine may be adjusted using the user modification of the engine-suggested codes as feedback, and the adjusted natural language understanding engine may be applied to automatically derive a second set of engine-suggested medical billing codes for the patient encounter, which may be presented for user review in the GUI before finalizing coding of the encounter.