Evidence map›Paper›PMID 36736957›Full record

ArticleThe journal of allergy and clinical immunology. In practice2023

Digital Antibiotic Allergy Decision Support Tool Improves Management of β-Lactam Allergies.

Theresa B Dunham, Rebecca M Gardner, Elizabeth A Lippner, Danielle E Fasani, Elwyn Moir, Bonnie Halpern-Felsher, Vandana Sundaram, Anne Y Liu

Abstract read
In one paragraph

Article in The journal of allergy and clinical immunology. In practice, 2023. 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. Developing and disseminating an electronic penicillin allergy de-labelling tool using the model for improvement framework.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2024
    Article
  2. Article
  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

8 authors.

Theresa B DunhamDivision of Allergy, Immunology, and Rheumatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, Calif. Electronic address: theresa.dunham24@gmail.com.
Rebecca M GardnerQuantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, Calif.
Elizabeth A LippnerDivision of Allergy and Immunology, Department of Pediatrics, Anne and Robert H. Lurie Children's Hospital and Northwestern Feinberg School of Medicine, Chicago, Ill.
Danielle E FasaniDepartment of Pharmacy, Stanford Health Care, Stanford, Calif.
Elwyn MoirClinical Observation and Medical Transcription Program, Stanford, Calif.
Bonnie Halpern-FelsherDivision of Adolescent Medicine, Department of Pediatrics, Stanford University, Palo Alto, Calif.
Vandana SundaramQuantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, Calif.
Anne Y LiuDivision of Allergy, Immunology, and Rheumatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, Calif; Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, Calif.

Funding

Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
Stanford BSSR Pre-Doctoral Training Program at the Intersection of Data Sciences with Behavioral, Social, and Population Health ResearchT32HL151323 · NHLBI · STANFORD UNIVERSITY · PI Michelle Christina Odden, David H Rehkopf · 2020 to 2026
$1.6M
NCATS NIH HHS UL1 TR001085NHLBI NIH HHS T32 HL151323
6 · The paper itself

Abstract

backgroundFrontline providers frequently make time-sensitive antibiotic choices, but many feel poorly equipped to handle antibiotic allergies.

objectiveWe hypothesized that a digital decision support tool could improve antibiotic selection and confidence when managing β-lactam allergies.

methodsA digital decision support tool was designed to guide non-allergist providers in managing patients with β-lactam allergy labels. Non-allergists were asked to make decisions in clinical test cases without the tool, and then with it. These decisions were compared using paired t tests. Users also completed surveys assessing their confidence in managing antibiotic allergies.

resultsThe tool's algorithm was validated by confirming its recommendations aligned with that of five allergists. Non-allergist providers (n = 102) made antibiotic management decisions in test cases, both with and without the tool. Use of the tool increased the proportion of correct decisions from 0.41 to 0.67, a difference of 0.26 (95% CI, 0.22-0.30; P < .001). Users were more likely to give full-dose antibiotics in low-risk situations, give challenge doses in medium-risk situations, and avoid the antibiotic and/or consult allergy departments in high-risk situations. A total of 98 users (96%) said the tool would increase their confidence when choosing antibiotics for patients with allergies.

conclusionsA point-of-care clinical decision tool provides allergist-designed guidance for non-allergists and is a scalable system for addressing antibiotic allergies, irrespective of allergist availability. This tool encouraged appropriate antibiotic use in low- and medium-risk situations and increased caution in high-risk situations. A digital support tool should be considered in quality improvement and antibiotic stewardship efforts.

Indexed as

Drug HypersensitivityHypersensitivityAnti-Bacterial Agentsbeta-LactamsHumansPenicillinsSurveys and QuestionnairesAnti-Bacterial Agentsbeta-LactamsPenicillinsAntibiotic allergyDigital toolPenicillin allergyβ-Lactam allergy

Identifiers

PMID36736957
PMCPMC10085826

What OpenQuestion holds

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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.