Abstract: A computer system increases the efficiency with which billing codes may be generated based on a chart, such as a medical chart. The computer system provides the chart to a computer-assisted coding (CAC) module, which produces an initial set of billing codes and an initial assessment of the accuracy and/or completeness of the codes. The computer system decides whether to send the initial set of billing codes to an initial human reviewer. If the computer system sends the initial set of billing codes to the initial human reviewer, then the initial human reviewer reviews the chart and the output of the CAC module, and attempts to fix errors in the CAC output. The system provides the chart and the current (initial or modified) codes to a final human reviewer, who may be more highly skilled than the initial human reviewer, for final verification and modification.

Abstract: A system includes a data record (such as an Electronic Medical Record (EMR)) and a user interface for modifying (e.g., storing data in) the data record. The data record includes both free-form text elements and discrete data elements. The user interface includes user interface elements for receiving free-form text data. In response to receiving free-form text data via the free-form text user interface elements, a suggested action is identified, such as a suggested action to take in connection with one of the discrete data elements of the data record. Output is generated representing the suggested action. A user provides input indicating acceptance or rejection of the suggested action. The suggested action may be performed in response to the user input.

Abstract: A graphical user interface, referred to herein as a virtual whiteboard, that provides both: (1) an automatically prioritized display of information related to a particular patient that is tailored to the current user of the system, and (2) a “scratch pad” area in which multiple users of the system may input free-form text and other data for sharing with other users of the system. When each user of the system accesses the virtual whiteboard, the system: (1) automatically prioritizes the patient information based on characteristics of the user and displays the automatically prioritized patient information to that user, and (2) displays the contents of the scratch pad to the user. As a result, the whiteboard displays both information that is tailored to the current user and information that is common to all users (i.e., not tailored to any particular user).

Abstract: Speech is transcribed to produce a transcript. At least some of the text in the transcript is encoded as data. These codings may be verified for accuracy and corrected if inaccurate. The resulting transcript is provided to a decision support system to perform functions such as checking for drug-drug, drug-allergy, and drug-procedure interactions, and checking against clinical performance measures (such as recommended treatments). Alerts and other information output by the decision support system are associated with the transcript. The transcript and associated decision support output are provided to a physician to assist the physician in reviewing the transcript and in taking any appropriate action in response to the transcript.

Abstract: A computer system uses a search engine to search a dataset using an initial query provided by a user and thereby to produce initial search results. The system enables the user to select portions of the initial search results. The system identifies metadata associated with the selected portions, and displays information representing that metadata in a form that is easily understandable by a person not trained in the annotation system in which the search results are encoded. The user may instruct the system to add one or more of the displayed metadata elements to the initial query, in response to which the system may add the specified metadata elements to the initial query to produce a modified query. The system may search the dataset using the modified query and thereby produce modified search results. The process may be repeated as desired by the user to further refine the search results.

Abstract: A method for selective modification to one of a plurality of components includes receiving, by an engine, a draft transcript including at least one concept content. The method includes accessing, by a first component in a plurality of components executed by the engine, a mapping between content data and codes to identify a code mapped to the at least one concept content. The method includes modifying the draft transcript to include the identified code. The method includes receiving input representing a status of the identified code. The method includes accessing a data structure storing an indication that the first component identified the code. The method includes modifying a reliability score for the first component. The method includes determining that the first component has a reliability score that fails to satisfy a predetermined threshold. The method includes modifying execution of the first component, based on the determination.

Abstract: Inputs provided into user interface elements of an application are observed. Records are made of the inputs and the state(s) the application was in while the inputs were provided. For each state, a corresponding language model is trained based on the input(s) provided to the application while the application was in that state. When the application is next observed to be in a previously-observed state, a language model associated with the application's current state is applied to recognize speech input provided by a user and thereby to generate speech recognition output that is provided to the application. An application's state at a particular time may include the user interface element(s) that are displayed and/or in focus at that time, and is determined by an operating system hooking component embedded in the automatic speech recognition system.

Abstract: A system includes a data record (such as an Electronic Medical Record (EMR)) and a user interface for modifying (e.g., storing data in) the data record. The data record includes both free-form text elements and discrete data elements. The user interface includes user interface elements for receiving free-form text data. In response to receiving free-form text data via the free-form text user interface elements, a suggested action is identified, such as a suggested action to take in connection with one of the discrete data elements of the data record. Output is generated representing the suggested action. A user provides input indicating acceptance or rejection of the suggested action. The suggested action may be performed in response to the user input.

Abstract: Inputs provided into user interface elements of an application are observed. Records are made of the inputs and the state(s) the application was in while the inputs were provided. For each state, a corresponding language model is trained based on the input(s) provided to the application while the application was in that state. When the application is next observed to be in a previously-observed state, a language model associated with the application's current state is applied to recognize speech input provided by a user and thereby to generate speech recognition output that is provided to the application. An application's state at a particular time may include the user interface element(s) that are displayed and/or in focus at that time, and is determined by an operating system hooking component embedded in the automatic speech recognition system.

Abstract: An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

Abstract: Speech is transcribed to produce a transcript. At least some of the text in the transcript is encoded as data. These codings may be verified for accuracy and corrected if inaccurate. The resulting transcript is provided to a decision support system to perform functions such as checking for drug-drug, drug-allergy, and drug-procedure interactions, and checking against clinical performance measures (such as recommended treatments). Alerts and other information output by the decision support system are associated with the transcript. The transcript and associated decision support output are provided to a physician to assist the physician in reviewing the transcript and in taking any appropriate action in response to the transcript.

Abstract: Methods and systems are disclosed for tracking quality measures in abstracted documents. Embodiments include, determining, based on the abstracted content, a quality measure category, obtaining a quality measure definition corresponding to a quality measure included in the determined quality measure category, determining, based on keywords corresponding to the criterion, whether a portion of the abstracted content satisfies a criterion, recording, in association with the criterion, a reference to the portion of the abstracted content that satisfies the criterion; and selectively generating, a report including the query corresponding to the criterion, a query response, and the portion of the abstracted content satisfying the criterion.

Abstract: Methods, systems, and software are disclosed for providing rule handling functionality in a distributed transcription environment. Some embodiments provide client-server workflow management for providing and supporting distributed transcription services. Other embodiments provide audio-to-text synchronization to support certain transcription functionality. Still other embodiments provide logging functionality to support quality, personnel, billing, and/or other enterprise tasks. And other embodiments provide functionality to support rule generation, editing, validation, and/or execution.

Abstract: Non-verbalized tokens, such as punctuation, are automatically predicted and inserted into a transcription of speech in which the tokens were not explicitly verbalized. Token prediction may be integrated with speech decoding, rather than performed as a post-process to speech decoding.

Abstract: A computer-based system includes a computer-processable definition of a region in a data set. The system identifies a region of the data set based on the definition of the region. The system provides output to a user representing a question and the identified region of the data set. The system may also automatically generate an answer to the question based on the question and the data set, and provide output to the user representing the answer. The system may generate the answer based on a subset of the data set, and provide output to the user representing the subset of the data set. The user may provide feedback on the first answer to the system, which the system may use to improve subsequent answers to the same and other questions, and to disable the system's automatic question-answering function in response to disagreement between the user and the system.

Abstract: Embodiments of the present invention are directed to computer systems for implementing dynamic, data-driven workflows within healthcare and other environments. Such a system may include a computer-processable definition of one or more workflows. Each workflow definition may define various aspects of the corresponding workflow, such as the data required by the workflow, a process for extracting such data from a variety of structured and/or unstructured data sources, a set of process steps to be performed within the workflow, and a condition for triggering the workflow. The system may use the workflow definition to extract the data required by the workflow and to perform the workflow's process steps on the extracted data in response to determining that the workflow's trigger condition has been satisfied. The workflow may change in response to changes in data extracted by the workflow.

Abstract: An automatic speech recognition system includes an audio capture component, a speech recognition processing component, and a result processing component which are distributed among two or more logical devices and/or two or more physical devices. In particular, the audio capture component may be located on a different logical device and/or physical device from the result processing component. For example, the audio capture component may be on a computer connected to a microphone into which a user speaks, while the result processing component may be on a terminal server which receives speech recognition results from a speech recognition processing server.

Abstract: A system includes a document corpus containing structured documents, which contain both text and annotations of the text. The system also includes a search engine which is adapted to perform structured searches of the structured documents. As new types of annotations are added to the system, the search engine is updated automatically to become capable of performing structured searches for the new types of annotations. For example, if a new natural language processing (NLP) component, adapted to generate annotations of a new type, is added to the system, then the system automatically updates a query language to include a definition of the new type of annotation. The search engine may then immediately be capable of processing structured queries which refer to the new type of annotation.

Abstract: A method for dynamic de-identification of a document includes generating a document including a tag associated with an element including protected health information, the tag including at least one instruction for rendering the element. The method includes identifying a level of authorization of a user requesting access to the generated document. The method includes rendering the document for display to the user according to the at least one instruction in the tag, based on the determined level of authorization.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.