Cerner Innovation, Inc.

Steven S Crooks

Christopher S Finn

David P McCallie, Jr

David J O'Larte

Margaret Cushing Kolm

Thomas C Gifford

J D Tyler

Michael Alan Ash

Savitha Venkat

Chad A Cole

Tonja McCord

Anubha Garg

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.

Duplication detection in clinical documentation during drafting

Methods, computer systems, and computer storage media are provided for providing real-time analysis and annotation of clinical documents in a distributed system. A clinical transformation session is opened at a clinical transformation server maintaining sessions for one or more editors and agents operating on a clinical document. Sequences of operations on the clinical document are stored at a memory accessible by the server. At least a portion of the clinical document is analyzed in real-time to provide annotations and other document modifications to each of the one or more editors having a session at the server. Parallel annotations or modifications are resolved and a synchronized view of the clinical document is maintained based on operational transformation.

Real-time collaborative clinical document analysis and editing

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.

Duplication detection in clinical documentation to update a clinician

Methods, systems, and computer-readable media are provided to detect similarities in clinical documents that might be inaccurate or inappropriate. A first clinical document and a second clinical document that are to be compared are identified. This identification of the documents is based on times associated with the first and second clinical documents, an identity of clinicians who authored the first and second clinical documents, an identity of patients associated with the first and second clinical documents, a type of the first and second clinical documents, or contents of the first and second clinical documents. The first clinical document is compared to a portion of the second clinical document. A report is automatically generated, where the report indicates the similarities between the portion of the first clinical document and the portion of the second clinical document that are potentially inaccurate or inappropriate.

Duplication detection in clinical documentation

A system and method for generating interactive visualizations of clinical relationships is provided. The method includes determining what entities have had some clinical contact with an entity of interest and collecting data regarding each entity and each entity's contacts with the entity of interest. The collected data can be filtered to remove unwanted entities and properties. Algorithms are applied to generate clinical relevance scores, which represent the relationship between the entities and the entity of interest. In addition, each entity is assigned components that allow for some executable behavior when an entity is selected in a display. Finally, the appropriate visualization is selected and a display of the relationships is generated.

System and method for creating a visualization indicating relationships and relevance to an entity

A computer-implemented method for facilitating placement of health care order entry is provided. The method includes receiving input indicative of a desired healthcare order. The order has certain terms therein that are normalized. The method also finds possible order matches for the normalized terms, and calculates a rough score for the possible order matches. The method refines the rough score with a rough score adjustment, and then ranks the found possible order matches from the most-likely to match the desired order to the least-likely based upon the refined rough score. These possible order matches can then be displayed to the user for selection.

Automated order entry system and method

A system and associated methods for orchestrating a collaboration session are disclosed. One method involves orchestrating a collaboration session between a requesting clinician and another clinician where information is exchanged electronically. According to the method, requests for collaboration sessions are received by a computer system from the requesting clinician, with a given request related to a piece of patient-focused clinical data. Each request is analyzed to build a roster of potentially available clinicians for collaboration. A collaboration session is then facilitated between the requesting clinician and one or more of the potentially available clinicians on the roster.

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Gladstone, MO, United States of America

Steven S Crooks