Evidence map›Paper›PMID 41136878›Full record

ReviewCurrent allergy and asthma reports2025

Using the Electronic Health Record to Facilitate Drug Allergy Delabeling.

Matthew J Molloy, Adam P Yan, Averi E Wilson, Jonathan Beus, Lauren M Hess

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Current allergy and asthma reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

5 authors.

Matthew J MolloyDivisions of Hospital Medicine and Biomedical Informatics, Department of Pediatrics, University of Cincinnati College of Medicine and Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. Matthew.Molloy@cchmc.org.
Adam P YanDivision of Hematology/Oncology, The Hospital for Sick Children, Toronto, ON, Canada.
Averi E WilsonClinical Informatics Center, Division of Pediatric Hospital Medicine, Department of Pediatric, University of Texas Southwestern, Dallas, TX, USA.
Jonathan BeusDepartment of Information Systems and Technology, Children's Healthcare of Atlanta and Division of Hospital Medicine, Department of Pediatrics, Emory University, Atlanta, GA, USA.
Lauren M HessDivision of Pediatric Hospital Medicine, Department of Pediatrics, Baylor College of Medicine, Texas children's Hospital, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThere is a growing number of allergy delabeling programs across diverse clinical specialties and care settings. The electronic health record (EHR) can be leveraged to facilitate allergy delabeling. The purpose of this review is to describe EHR tools that have been used in allergy delabeling programs. We also provide recommendations for organizations considering EHR-based allergy delabeling workflows that incorporate clinical informatics best practices. RECENT

findingsRecent literature describes several EHR tools used in delabeling. These tools can be organized around the steps of the allergy delabeling workflow: 1. Identify eligible patients, 2. Risk stratify, 3. Evaluation and testing, 4. Documentation of outcome, 5. Delabeling, and 6. Allergy label reconciliation. Standardized EHR tools across the allergy delabeling workflow can lead to successful delabeling and support of diverse stakeholders. Partnering with EHR vendors presents an opportunity to make these tools readily available and improve allergy documentation.

Indexed as

Drug HypersensitivityElectronic Health RecordsDocumentationHumansWorkflowAllergy delabelingClinical decision supportClinical informaticsElectronic health record

Identifiers

PMID41136878
PMCPMC12552388

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.