Dictaphone Corporation.

Nuance Communications, Inc.

Deliverhealth Solutions LLC

Escription, Inc.

Robert G Titemore

Keith W Boone

Harry J Ogrinc

Sean Gervais

Roubik Manoukian

Jeffrey G Hopkins

Cameron Fordyce

Sunitha Chaparala

Roger Scott Zimmerman

George Zavaliagkos

Paul Egerman

Alwin B Carus

Melissa MacPherson

Brian Wilson

Stefaan Heyvaert

Don Fonza

David Speth

Tom Deplonty

Ray Rankins

A computer program product, for automatically editing a medical record transcription, resides on a computer-readable medium and includes computer-readable instructions for causing a computer to obtain a first medical transcription of a dictation, the dictation being from medical personnel and concerning a patient, analyze the first medical transcription for presence of a first trigger phrase associated with a first standard text block, determine that the first trigger phrase is present in the first medical transcription if an actual phrase in the first medical transcription corresponds with the first trigger phrase, and insert the first standard text block into the first medical transcription.

Insertion of standard text in transcription

In a method for validating data, a text of a document is received. At least one fact is extracted from the text. At least one expert refinement is merged with the at least one fact to create at least one modified fact. The at least one modified fact is provided for a review. An expert refinement to the at least one modified fact is captured in response to the review. A superset document based on the at least one pre-existing refinement and the expert refinement is stored.

Method, system, and apparatus for validation

A system and method may be disclosed for facilitating the creation or modification of a document by providing a mechanism for locating relevant data from external sources and organizing and incorporating some or all of said data into the document. In the method for reusing data, there may be a set of documents that may be queried, where each document may be divided into a plurality of sections. A plurality of section text groups may be formed based on the set of documents, where each section text group may be associated with a respective section from the plurality of sections and each section group includes a plurality of items. Each item may be associated with a respective section from each document of the set of documents. A selected item within a selected section text group may be focused. The selected item may be extracted to a current document. The current document may be exported to a host application.

Method, system, and computer-readable medium for creating a new electronic document from an existing electronic document

Method, system and apparatus for data reuse

Method, system, and apparatus for data reuse

Insertion of standard text in transcriptions

A system and method for automatically reusing document text (e.g. repeated phrases or lists) in a newly created document having a predetermined document type (e.g. medical record). The present invention determines whether business rules exist for the predetermined document type associated with the newly created document. If business rules for the predetermined document type exist, the present invention determines whether the user has previously requested document text reuse for the newly created document. If the user has not previously requested document text reuse for the newly created document, the present invention selects document text from one or more stored documents in accordance with the business rules for the predetermined document type corresponding to the newly created document. The present invention then automatically inserts the selected document text into the newly created document.

System and method for auto-reuse of document text

The invention includes a medical document handling system and method and automated coding systems and methods for assigning predetermined medical codes to medical documents based on the documents' contents. The invention functions by analyzing electronic medical records and extracting medical information using natural language processing and machine learning. The system collects and amalgamates medical documentation in various formats from multiple sources and locations, normalizes the information, analyzes the information, recognizes information indicating contents corresponding to classification codes, assigns classification codes, and presents information in context correlated to medical records for billing and other purposes.

Systems and methods for coding information

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Lexington, MA, United States of America

Robert G Titemore