Allscripts Software, LLC

Other

Altera Digital Health Inc.

2bprecise Technologies, LLC

Assaf Halevy

Joel Diamond

Eyal Greenberg

Shiri Ben-Tal

David Thomas Windell

Robert Wartenfeld

Brad Emery

Gary S Gartner

Shiri Ben Tal

Davis Walp

Jeri-lynn Gehr

Ellen Loch

Surj Kant Ramlogan

One or more preferred embodiments facilitate use of patient panomics indications to select treatments that will provide optimal results. One or more preferred embodiments relate to a practical ontology for the panomics domain that is utilized to support use of patient panomics indications. In accordance with one or more preferred implementations, a cancer panomics ontology facilitates replacement of traditional cancer stratification by organs (e.g. lung, breast, liver cancer) with cancer stratification by tumor biomarkers (e.g. HER2 mutations). In accordance with one or more preferred implementations, a panomic ontology is utilized to facilitate functionality of a precision medical system.

Panomics ontology

Providing healthcare services based on the combination of data from electronic healthcare records (EHRs) and community patient data includes: retrieving EHR data from an EHR database for a patient; retrieving community patient data for the patient; and providing clinical decision support for a healthcare provider at a computing device of the healthcare provider by interjecting, into a clinical workflow that utilizes the retrieved EHR data, the retrieved community patient data such that the clinical workflow utilizes the retrieved EHR data and the retrieved community patient data without importing the retrieved community patient data into the EHR database, and providing results of the workflow to the healthcare provider in a user interface at the computing device. The EHR data joined with the community patient data is actionable without importing the community patient data into the EHR database.

Joining patient EHR data with community patient data

Described herein are various technologies pertaining to storing and transmitting formatted genetic test results. A server computing device receives genetic test results from several genetics laboratories, where the genetic test results are in different formats. The server computing device formats each of the genetic test results such that the resultant formatted genetic test results have a uniform format. The server computing device receives a query from a client computing device that is displaying a graphical user interface (GUI) of an electronic health records application (EHR), and searches over the formatted genetic test results to generate search results, wherein the query includes an identifier for a patient whose medical record is being displayed in the GUI of the EHR. The server computing device transmits the search results to the client computing device, whereupon the search results are displayed on the display of the client computing device.

Computing system for genetic databank application

Described herein are various technologies pertaining an electronic health record application (EHR). The EHR has a rules engine that is configured to execute a plurality of rules corresponding to respective genetic disorders. The rules receive clinical data as input, and each rule is configured to output an indication as to whether or not a patient is a candidate for genetic testing for a genetic disorder.

Computer-executable application that is configured to process cross-clinical genomics data

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Pittsburgh, PA, United States of America

Assaf Halevy