Formal representation of patients’ care context data: the path to improving the electronic health record

Author:

Colicchio Tiago K1ORCID,Dissanayake Pavithra I1,Cimino James J1ORCID

Affiliation:

1. Informatics Institute, University of Alabama at Birmingham, USA

Abstract

Abstract Objective To develop a collection of concept-relationship-concept tuples to formally represent patients’ care context data to inform electronic health record (EHR) development. Materials and Methods We reviewed semantic relationships reported in the literature and developed a manual annotation schema. We used the initial schema to annotate sentences extracted from narrative note sections of cardiology, urology, and ear, nose, and throat (ENT) notes. We audio recorded ENT visits and annotated their parsed transcripts. We combined the results of each annotation into a consolidated set of concept-relationship-concept tuples. We then compared the tuples used within and across the multiple data sources. Results We annotated a total of 626 sentences. Starting with 8 relationships from the literature, we annotated 182 sentences from 8 inpatient consult notes (initial set of tuples = 43). Next, we annotated 232 sentences from 10 outpatient visit notes (enhanced set of tuples = 75). Then, we annotated 212 sentences from transcripts of 5 outpatient visits (final set of tuples = 82). The tuples from the visit transcripts covered 103 (74%) concepts documented in the notes of their respective visits. There were 20 (24%) tuples used across all data sources, 10 (12%) used only in inpatient notes, 15 (18%) used only in visit notes, and 7 (9%) used only in the visit transcripts. Conclusions We produced a robust set of 82 tuples useful to represent patients’ care context data. We propose several applications of our tuples to improve EHR navigation, data entry, learning health systems, and decision support.

Funder

Informatics Institute of the University of Alabama at Birmingham

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference35 articles.

1. To combat physician burnout and improve care, fix the electronic health record;Wachter;J Harv Bus Rev,2018

2. Health information technology as a learning health system: call for a national monitoring system;Colicchio;Learn Health Sys,2019

3. Electronic health record usability issues and potential contribution to patient harm;Howe;JAMA,2018

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