Abstract: Techniques are provided whereby a clarification request may be generated with a clinical documentation improvement (CDI) system for resolution by a clinician, and notification of the clarification request may be transmitted to a medical coding system. At a medical coding system, notification may be received of a clarification request generated at a CDI system for resolution by a clinician. In some embodiments, the medical coding system may be a computer-assisted coding (CAC) system.

Abstract: Techniques for training a natural language understanding (NLU) engine may include generating a first annotation of free-form text documenting a healthcare patient encounter and a link between the first annotation and a corresponding portion of the text, using the NLU engine. A second annotation of the text and a link between the second annotation and a corresponding portion of the text may be received from a human user. The first annotation and its corresponding link may be merged with the second annotation and its corresponding link. Training data may be provided to the engine in the form of the text and the merged annotations and links.

Abstract: Techniques for training a natural language understanding (NLU) engine may include generating a first annotation of free-form text documenting a healthcare patient encounter and a link between the first annotation and a corresponding portion of the text, using the NLU engine. A second annotation of the text and a link between the second annotation and a corresponding portion of the text may be received from a human user. The first annotation and its corresponding link may be merged with the second annotation and its corresponding link. Training data may be provided to the engine in the form of the text and the merged annotations and links.

Abstract: Techniques are provided whereby a clarification request may be generated with a clinical documentation improvement (CDI) system for resolution by a clinician, and notification of the clarification request may be transmitted to a medical coding system. At a medical coding system, notification may be received of a clarification request generated at a CDI system for resolution by a clinician. In some embodiments, the medical coding system may be a computer-assisted coding (CAC) system.

Abstract: Techniques for use in medical coding include applying a natural language understanding engine to a free-form text documenting at least one clinical patient encounter to generate a set of one or more medical billing codes for the patient encounter. A user interface may be provided, configured to allow one or more human users to review and correct the generated set of medical billing codes. Within the user interface, in response to user selection of a first medical billing code of the generated set of medical billing codes, at least a portion of a government-authorized codebook for the first medical billing code may be displayed, and a position of the first medical billing code may be indicated in the displayed portion of the codebook.

Abstract: Techniques are provided whereby a clarification request may be generated with a clinical documentation improvement (CDI) system for resolution by a clinician, and notification of the clarification request may be transmitted to a medical coding system. At a medical coding system, notification may be received of a clarification request generated at a CDI system for resolution by a clinician. In some embodiments, the medical coding system may be a computer-assisted coding (CAC) system.

Abstract: Techniques for use in medical coding include applying a natural language understanding engine to a free-form text documenting at least one clinical patient encounter to generate a set of one or more medical billing codes for the patient encounter. A user interface may be provided, configured to allow one or more human users to review and correct the generated set of medical billing codes. Within the user interface, in response to user selection of a first medical billing code of the generated set of medical billing codes, at least a portion of a government-authorized codebook for the first medical billing code may be displayed, and a position of the first medical billing code may be indicated in the displayed portion of the codebook.

Abstract: Techniques for training a natural language understanding (NLU) engine may include generating a first annotation of free-form text documenting a healthcare patient encounter and a link between the first annotation and a corresponding portion of the text, using the NLU engine. A second annotation of the text and a link between the second annotation and a corresponding portion of the text may be received from a human user. The first annotation and its corresponding link may be merged with the second annotation and its corresponding link. Training data may be provided to the engine in the form of the text and the merged annotations and links.

Abstract: Systems and methods for producing and presenting annotations of clinical documents in a rich format are described, for instance for use with medical billing procedures. An initial XHTML document documenting a medical patient encounter and having rich formatting is used to generate a plain text document. A clinical language understanding system generates annotations, such as medical codes, which are used to annotate the XHTML document. The annotated XHTML document is then presented to a user, thus displaying for the user the annotations while retaining the rich formatting of the initial XHTML document.

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.

Abstract: Techniques for use in medical coding include applying a natural language understanding engine to a free-form text documenting at least one clinical patient encounter to generate a set of one or more medical billing codes for the patient encounter. A user interface may be provided, configured to allow one or more human users to review and correct the generated set of medical billing codes. Within the user interface, in response to user selection of a first medical billing code of the generated set of medical billing codes, at least a portion of a government-authorized codebook for the first medical billing code may be displayed, and a position of the first medical billing code may be indicated in the displayed portion of the codebook.

Abstract: Techniques are provided whereby a clarification request may be generated with a clinical documentation improvement (CDI) system for resolution by a clinician, and notification of the clarification request may be transmitted to a medical coding system. At a medical coding system, notification may be received of a clarification request generated at a CDI system for resolution by a clinician. In some embodiments, the medical coding system may be a computer-assisted coding (CAC) system.

Abstract: Techniques for training a natural language understanding (NLU) engine may include generating a first annotation of free-form text documenting a healthcare patient encounter and a link between the first annotation and a corresponding portion of the text, using the NLU engine. A second annotation of the text and a link between the second annotation and a corresponding portion of the text may be received from a human user. The first annotation and its corresponding link may be merged with the second annotation and its corresponding link. Training data may be provided to the engine in the form of the text and the merged annotations and links.

Abstract: Systems and methods for producing and presenting annotations of clinical documents in a rich format are described, for instance for use with medical billing procedures. An initial XHTML document documenting a medical patient encounter and having rich formatting is used to generate a plain text document. A clinical language understanding system generates annotations, such as medical codes, which are used to annotate the XHTML document. The annotated XHTML document is then presented to a user, thus displaying for the user the annotations while retaining the rich formatting of the initial XHTML document.

Abstract: Techniques for training a natural language understanding (NLU) engine may include generating a first annotation of free-form text documenting a healthcare patient encounter and a link between the first annotation and a corresponding portion of the text, using the NLU engine. A second annotation of the text and a link between the second annotation and a corresponding portion of the text may be received from a human user. The first annotation and its corresponding link may be merged with the second annotation and its corresponding link. Training data may be provided to the engine in the form of the text and the merged annotations and links.