Evidence map›Paper›PMID 41737564›Full record

ArticlePediatric quality & safety

Improving Structured Handoff Documentation in a Pediatric Emergency Department.

Deborah Hammett, Rebecca Matta, Jody Kieffer, Jillian Savage, Courtney Nelson

Abstract read
In one paragraph

Article in Pediatric quality & safety. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Deborah HammettFrom the Division of Emergency Medicine, Nemours Children's Health, Wilmington, Del.
Rebecca MattaDivision of Emergency Medicine, New York University Langone Hospital/Bellevue Hospital Center, New York, NY.
Jody KiefferFrom the Division of Emergency Medicine, Nemours Children's Health, Wilmington, Del.
Jillian SavageFrom the Division of Emergency Medicine, Nemours Children's Health, Wilmington, Del.
Courtney NelsonFrom the Division of Emergency Medicine, Nemours Children's Health, Wilmington, Del.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The I-PASS handoff tool guides provider handoffs and reduces adverse events in the inpatient setting. Transitions of care occur frequently in the emergency department (ED), and the unpredictable environment can lead to less structured handoffs. Our goal was to increase the percentage of handoff notes that include all 4 I-PASS components by 20% within 6 months. Methods: We developed a handoff note template for the pediatric ED that included 4 key I-PASS elements: illness severity, patient care summary, action list, and situational awareness/contingency planning. Our primary outcome measure was the percentage of handoff notes that contained all 4 I-PASS elements. Our process measure was the percentage of handoff notes that used the template. Our balancing measure was the percentage of handoffs with no note. We analyzed a random sample of 20 charts monthly during our preimplementation (August 2021-July 2022) and postimplementation (August 2022-January 2024) phases. We completed monthly Plan-Do-Study-Act cycles to review note usage and identify obstacles to use. Process improvements included modifying the note template, enhancing accessibility within the electronic medical record, and designating computer workstations for completing handoff notes. Results: We assessed 240 handoff notes to determine the preimplementation baseline and evaluated 360 handoff notes postimplementation. Following implementation, 63.0% of handoff notes contained 4 I-PASS elements, compared with 0% before our intervention. Similarly, use of handoff templates increased to 82.0% from 0%. There was no change in handoffs without documentation. Conclusions: Using a standardized note template for provider handoff improved adherence with the I-PASS handoff tool in the pediatric ED.

Identifiers

PMID41737564
PMCPMC12928866

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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.