Cerner Innovation, Inc.

J D Tyler

Michael Alan Ash

Thomas C Gifford

Christopher S Finn

Margaret Cushing Kolm

David J O'Larte

Steven S Crooks

Heather Owen

David P McCallie, Jr

Brian J Lancaster

David Cohen

Pramod Pagadala

Savitha Venkat

Chad A Cole

Daniel Stocksick

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, systems, and computer-storage media are provided for facilitating the care of a patient by a multi-disciplinary care team. A graphical user interface presents one or more clinical problems associated with a patient. For each clinical problem, actionable care team icons are presented that, among other things, identify care teams responsible for caring for the clinical problem and any actions taken by the care teams to address the clinical problem.

Multi-disciplinary team workspace

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.

Dynamic association and documentation

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

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Leawood, KS, United States of America

J D Tyler