Rapid identification and phenotyping of nonalcoholic fatty liver disease patients using a machine-based approach in diverse healthcare systems.

Nonalcoholic fatty liver disease (NAFLD) is the most common global cause of chronic liver disease and remains under-recognized within healthcare systems. Therapeutic interventions are rapidly advancing for its inflammatory phenotype, nonalcoholic steatohepatitis (NASH) at all stages of disease. Diagnosis codes alone fail to recognize and stratify at-risk patients accurately.

Relationships Between Hearing-Related and Health-Related Variables in Academic Progress of Children With Unilateral Hearing Loss.

Purpose: School-age children with unilateral hearing loss are at an increased risk of exhibiting academic difficulties. Yet, approximately half of children with unilateral hearing loss will not require additional support. There is a dearth of information to assist in determining which of these children will express academic deficits and which will not.

The Use of Electronic Health Records for Behavioral Phenotyping of School-Age Children With Unilateral Hearing Loss: A Methodological Approach.

Purpose: This methodological study describes a technique for extracting information from de-identified electronic health records (EHRs) to identify occurrences of permanent unilateral hearing loss (UHL) and associated educational comorbidities.

Method: This was an exploratory methodological study utilizing approximately 3.3 million de-identified medical records.

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

Background: Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding. Autopsy reports contain narrative text describing scene evidence and medical history (similar to preliminary death scene investigation reports) and may serve as early data sources for identifying fatal drug overdoses. To facilitate timely fatal overdose reporting, natural language processing was applied to narrative texts from autopsies.

Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems.

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US.

Real-time clinical note monitoring to detect conditions for rapid follow-up: A case study of clinical trial enrollment in drug-induced torsades de pointes and Stevens-Johnson syndrome.

Identifying acute events as they occur is challenging in large hospital systems. Here, we describe an automated method to detect 2 rare adverse drug events (ADEs), drug-induced torsades de pointes and Stevens-Johnson syndrome and toxic epidermal necrolysis, in near real time for participant recruitment into prospective clinical studies. A text processing system searched clinical notes from the electronic health record (EHR) for relevant keywords and alerted study personnel via email of potential patients for chart review or in-person evaluation.

Improving the phenotype risk score as a scalable approach to identifying patients with Mendelian disease.

Objective: The Phenotype Risk Score (PheRS) is a method to detect Mendelian disease patterns using phenotypes from the electronic health record (EHR). We compared the performance of different approaches mapping EHR phenotypes to Mendelian disease features.

Materials And Methods: PheRS utilizes Mendelian diseases descriptions annotated with Human Phenotype Ontology (HPO) terms.

Breadcrumbs: Assessing the Feasibility of Automating Provider Documentation Using Electronic Health Record Activity.

This study assessed the feasibility of automating the generation of the outpatient encounter summary. We reviewed screen tracking video and log-file metadata from electronic health record (EHR) interactions based on two simulated encounters. We mapped the sequence of metadata to key concepts in the video to assess the precision with which the log files aligned with user activity and to generate the Breadcrumbs encounter summary (BES).