Evidence map›Paper›PMID 38222434›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2023

Semantically oriented EHR navigation with a patient specific knowledge base and a clinical context ontology.

Tiago K Colicchio, John D Osborne, Clementino V Do Rosario, Ankit Anand, Nicholas A Timkovich, Matthew C Wyatt, James J Cimino

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Tiago K ColicchioInformatics Institute, University of Alabama at Birmingham.
John D OsborneInformatics Institute, University of Alabama at Birmingham.
Clementino V Do RosarioInformatics Institute, University of Alabama at Birmingham.
Ankit AnandInformatics Institute, University of Alabama at Birmingham.
Nicholas A TimkovichInformatics Institute, University of Alabama at Birmingham.
Matthew C WyattInformatics Institute, University of Alabama at Birmingham.
James J CiminoInformatics Institute, University of Alabama at Birmingham.

Funding

Improving Electronic Health Record Usability and Usefulness with a Patient-Specific Clinical Knowledge BaseR21LM013401 · NLM · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CIMINO, JAMES J · 2021 to 2022
$355k
NLM NIH HHS R21 LM013401
6 · The paper itself

Abstract

Widespread adoption of electronic health records (EHR) in the U.S. has been followed by unintended consequences, overexposing clinicians to widely reported EHR limitations. As an attempt to fixing the EHR, we propose the use of a clinical context ontology (CCO), applied to turn implicit contextual statements into formally represented data in the form of concept-relationship-concept tuples. These tuples form what we call a patient specific knowledge base (PSKB), a collection of formally defined tuples containing facts about the patient's care context. We report the process to create a CCO, which guides annotation of structured and narrative patient data to produce a PSKB. We also present an application of our PSKB using real patient data displayed on a semantically oriented patient summary to improve EHR navigation. Our approach can potentially save precious time spent by clinicians using today's EHRs, by showing a chronological view of the patient's record along with contextual statements needed for care decisions with minimum effort. We propose several other applications of a PSKB to improve multiple EHR functions to guide future research.

Indexed as

Electronic Health RecordsNarrationHumansKnowledge Bases

Identifiers

PMID38222434
PMCPMC10785934

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.