US 11,842,161 B1
Systems and methods for enhancing natural language processing
Kanakasabha Kailasam, Olathe, KS (US); Douglas S. McNair, Seattle, WA (US); John Christopher Murrish, Overland Park, KS (US); David Cohen, Leawood, KS (US); Josh Smith, Kansas City, MO (US); Alex Vickers, Gladstone, MO (US); and Tanuj Gupta, Leawood, KS (US)
Assigned to Cerner Innovation, Inc., Kansas City, KS (US)
Filed by CERNER INNOVATION, INC., Kansas City, KS (US)
Filed on Aug. 11, 2021, as Appl. No. 17/399,622.
Application 17/399,622 is a continuation of application No. 16/284,844, filed on Feb. 25, 2019, granted, now 11,100,289.
Claims priority of provisional application 62/634,571, filed on Feb. 23, 2018.
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/30 (2020.01); G06F 40/205 (2020.01)
CPC G06F 40/30 (2020.01) [G06F 40/205 (2020.01)] 14 Claims
OG exemplary drawing
 
1. Computer storage media having computer-executable instructions embodied thereon that when executed, provide enhanced natural language processing that includes a set of actions comprising:
receiving a current electronic document with unstructured health-related data associated with an individual;
parsing and extracting at least one clinical condition within the unstructured health-related data using one or more natural language processing techniques;
identifying one or more clinical concepts related to the clinical condition using one or more clinical ontologies for the at least one clinical condition, each clinical ontology providing contextual relationships between the clinical condition and the one or more clinical concepts;
retrieving one or more portions of a longitudinal electronic health record (EHR) associated with the individual, the longitudinal EHR comprising documentation of at least one prior encounter and having some a structured data;
searching for one or more clinical concepts within the current electronic document and the longitudinal EHR and assigning a confidence value based on a statistical likelihood of whether the clinical condition matches the clinical concept, the confidence value comprising one of a positive, neutral, or negative state indicating a statistical likelihood the clinical condition matches the clinical concept is above, within, or below a threshold value;
based on whether the clinical condition has a sufficient confidence value, providing a notification, in real time, to a user of an application for entering the current electronic document, the notification either stating the clinical condition has a sufficient confidence value, the clinical condition has an insufficient confidence value, or requesting supplemental information to support a diagnosis for the clinical condition;
triggering a coding document quality process to check whether current documentation supports a given coding level assigned to the clinical condition, wherein determining whether the current documentation supports a given coding level comprises determining a high confidence value to a presence of a clinical code corresponding to the clinical condition; and
providing the notification when the current documentation supports a coding level.