Clinical report retrieval and/or comparison

Abstract

Instructions (108) cause a processor (104) to: classify a clinical report for a subject under evaluation by one of anatomical organ or disease; identify and retrieve clinical reports for the same subject from the healthcare data source(s); group the retrieved clinical report by one of anatomical organ or disease; select a group of the clinical report, wherein the group includes reports for a sameor related one of the anatomical organ or the disease; build a model that predicts semantic relationships between nodes in the reports in the selected group of reports based on one or more of extracted parameters or keywords; compare one of the parameter values or the keywords across the reports using the model; construct a graphical timeline of the reports; highlight differences in the parametervalues or the keywords based on a result of the compare; and visually present the graphical timeline with the highlighted differences.

Description

technical field [0001] The following generally relates to clinical report retrieval and / or comparison. Background technique [0002] Clinical text reports describe details from clinical processes such as admission, discharge, routine rounds, imaging studies, and laboratory report surveys. These reports contain different types of information about the patient's condition (e.g., diagnosis, treatment plan, prognosis, etc.), including unstructured patient details with valuable contextual insights into past and current health conditions and high-fidelity and Structured data that is typically measured on a regular basis. The structured values ​​(measurements) generally allow the clinician to make a timely assessment of the patient's state towards appropriate intervention. Furthermore, these values ​​can be used to determine treatment effects and predict the effectiveness of future interventions. Understanding patient conditions described in clinical reports and interpreting str...

AI Technical Summary

Problems solved by technology

Manually reviewing and interpreting clinical reports is often time-consuming and prone to human error

Furthermore, accessing the clinical reports archived in most EMR systems can be very challenging due to technical bottlenecks, and these systems often do not provide the ability to automatically compare longitudinal reports to extract clinically relevant connections that Connectivity informs clinicians of overall patient urgency and supports clinical decision making

Images