Abstract: Methods, systems, and computer-readable media are provided to detect similarities between two or more clinical documents. It is determined that a clinician is currently inputting data into a first clinical document that is associated with a patient. A selectable option is provided on a user interface into which the clinician is currently inputting the data. An indication is received that the selectable option has been selected by the clinician. An algorithm is applied to identify the second clinical document from a plurality of clinical documents. At least a portion of the inputted data in the first clinical document and at least a portion of data in the second clinical document are transformed to generate a new representation of the first clinical document that indicates the similarities that are potentially inaccurate or inappropriate between the first clinical document and the second clinical document.

Abstract: Methods, systems, and computer-storage media are provided for enabling a user to dynamically create associations and take actions with respect to a clinical finding associated with a patient. After selecting a clinical finding that is of interest in a first workflow application, a graphical user interface is automatically presented. The graphical user interface includes trending information for the clinical finding as well as information related to the clinical finding. The graphical user interface enables a clinician to associate the clinical finding with a current patient problem or a possible diagnosis related to the clinical finding. Additionally, the graphical user interface enables the clinician to take actions with respect to the clinical finding.

Abstract: Methods, systems, and computer storage media are provided for converting a source in a first terminology to a target in a different terminology. A source in a first terminology may be converted to a target in a second terminology using cross maps that map sources to all possible matching targets, probability data derived from frequency data illustrating a frequency of selection for targets in relation to specific sources, lexical matching algorithms indicating targets with highest lexical matches for specific sources, or a combination thereof. Any one, or a combination, of the data above may be used to identify a probabilistically most relevant target in a desired terminology.

Abstract: Methods, systems, and computer-readable media are provided for facilitating the voice-assisted creation of a shorthand clinical note on a mobile or tablet device. A microphone on the device is used to capture a conversation between a clinician and a patient. Clinically-relevant concepts in the conversation are identified, extracted, and temporarily presented on the device's touch screen interface. The concepts are selectable, and upon selection, the selected concept is populated into a clinical note display area of the touch screen interface. The shorthand clinical note may be used as a memory prompt for the later creation of a more comprehensive clinical note.

Abstract: Methods, systems, and computer-readable media are provided for determining and generating content items that provide patient information and content provided by, for example, a third-party content provider that is relevant to information associated with an open healthcare application. The content items are displayed in a separate display space from the healthcare application's user interface and dynamically change and update in response to changes in the information being displayed on the healthcare application's user interface. Additionally, the content items are actionable thereby enabling healthcare providers to address alerts, take actions, view supporting documentation, and the like.

Abstract: Methods, systems, and computer-readable media are provided to detect incremental changes in clinical documents associated with a patient. A user selection is received indicating that a user wants to compare two or more clinical documents that are associated with the patient or authored by the same clinician, enabling the user to become up-to-date on the patient's care. A first clinical document and a second clinical document are identified. For the first clinical document and the second clinical document, differences are algorithmically determined. The first clinical document is transformed into a new representation of the first clinical document. Further, the second clinical document is transformed into a new representation of the second clinical document. One or more of the new representations of the first and the second clinical documents are displayed, assisting the user to quickly find and understand the differences between the documents.

Abstract: Methods, systems, and computer-readable media are provided for determining and generating variably-sized display areas for presenting content items. The display areas include a notification bar that present icons representative of content items, a content item display area that displays content items, and a results display area that presents more detailed information concerning a particular content item.

Abstract: Methods, systems, and computer-readable media are provided for determining and generating content items that provide patient information and content provided by, for example, a third-party content provider that is relevant to information associated with an open healthcare application. The content items are displayed in a separate display space from the healthcare application's user interface and dynamically change and update in response to changes in the information being displayed on the healthcare application's user interface. Additionally, the content items are actionable thereby enabling healthcare providers to address alerts, take actions, view supporting documentation, and the like.

Abstract: Methods, systems, and computer storage media are provided for converting a source in a first terminology to a target in a different terminology. A source in a first terminology may be converted to a target in a second terminology using cross maps that map sources to all possible matching targets, probability data derived from frequency data illustrating a frequency of selection for targets in relation to specific sources, lexical matching algorithms indicating targets with highest lexical matches for specific sources, or a combination thereof. Any one, or a combination, of the data above may be used to identify a probabilistically most relevant target in a desired terminology.

Abstract: A computerized method and system for generation an immunization schedule for a person in healthcare environment is provided. The system receives a request for an immunization schedule for a person and obtains information from an electronic medical record of the person stored within a comprehensive healthcare system. The system obtains one or more immunization schedules and utilizes the information from the electronic medical record of the person and the immunization schedule to generate a customized immunization schedule for the person. In another embodiment, the system receives immunization information for a person and stores the immunization information in the electronic medical record of the person within a comprehensive healthcare system.

Abstract: A computerized method and system for generation an immunization schedule for a person in healthcare environment is provided. The system receives a request for an immunization schedule for a person and obtains information from an electronic medical record of the person stored within a comprehensive healthcare system. The system obtains one or more immunization schedules and utilizes the information from the electronic medical record of the person and the immunization schedule to generate a customized immunization schedule for the person. In another embodiment, the system receives immunization information for a person and stores the immunization information in the electronic medical record of the person within a comprehensive healthcare system.

Abstract: A device for modeling an integrated enterprise includes a first tool for constructing a model of the integrated enterprise and a second tool for analyzing calls, contained in the constructed model, between applications of the integrated enterprise and a database shared thereby. The call analysis tool identifies data attribute imbalances in calls between the applications of the integrated enterprise and the shared database. Data attribute imbalances result if the calls attempt to consume data which was never produced or if the calls produce data which is never consumed. The call analysis tool also generates producer/consumer maps of the data attributes used in the model, producer exception reports which identify data attributes which are consumed but never produced and consumer exception reports which identify data attributes which are produced but never consumed.

Abstract: A device for modeling an integrated enterprise includes a first tool for constructing a model of the integrated enterprise and a second tool for analyzing calls, contained in the constructed model, between applications of the integrated enterprise and a database shared thereby. The call analysis tool identifies data attribute imbalances in calls between the applications of the integrated enterprise and the shared database. Data attribute imbalances result if the calls attempt to consume data which was never produced or if the calls produce data which is never consumed. The call analysis tool also generates producer/consumer maps of the data attributes used in the model, producer exception reports which identify data attributes which are consumed but never produced and consumer exception reports which identify data attributes which are produced but never consumed.

Abstract: A device for modeling an integrated enterprise includes a first tool for constructing a model of the integrated enterprise and a second tool which validates compliance of documents constructed by the first tool with a set of standards. The documents which may be constructed by the first tool include an analysis interface control document (“ICD”) and a design ICD document. The second tool may then be used to selectively compare either the analysis ICD or the design ICD with selected ICD standards and generate an analysis ICD document standards exception report and a design ICD document standards exception report, respectively, which lists each variation of the analysis and design ICD documents from the selected ICD standards. The analysis and/or design ICD standards exception reports may subsequently be used as guides to correct errors in the analysis and/or design ICD documents causing the exceptions.

Abstract: A selected scenario of a design ICD document for an integrated enterprise is validated by examining each IDL call of each sequence diagram forming part of the selected scenario. A list of data attributes contained in one or more of the IDL calls are generated and each IDL call associated therewith is generated. A physical location to which each such IDL call is mapped is then associated with the IDL call. By analyzing the IDL calls and associated physical locations on a data attribute-by-data attribute basis, inconsistencies in the physical mapping of the data attributes to the databases forming an IIS for the integrated enterprise may be identified and subsequently corrected.

Abstract: A device for modeling an integrated enterprise includes a first tool for constructing a model of the integrated enterprise and a second tool for analyzing inter-application call sets contained in the constructed model. The second tool analyzes a selected inter-application call set by constructing a data attribute matrix having a row for each data attribute contained in at least one of the inter-application calls and a column for each one of the inter-application calls. The data attribute matrix is then marked to indicate which ones of the data attributes are contained in which ones of the selected inter-application calls. The constructed data attribute matrix may then be analyzed to identify improper association of data attributes with calls.