Evidence map›Paper›PMID 38071526›Full record

ArticleBMJ quality & safety2024

Retrospective cohort study of wrong-patient imaging order errors: how many reach the patient?

Jerard Z Kneifati-Hayek, Elias Geist, Jo R Applebaum, Alexis K Dal Col, Hojjat Salmasian, Clyde B Schechter, Noémie Elhadad, Joshua Weintraub, Jason S Adelman

Abstract read
In one paragraph

Article in BMJ quality & safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Jerard Z Kneifati-HayekDepartment of Medicine, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0002-8740-8409
Elias GeistColumbia University College of Physicians and Surgeons, New York, New York, USA.
Jo R ApplebaumDepartment of Medicine, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0002-4137-6069
Alexis K Dal ColColumbia University College of Physicians and Surgeons, New York, New York, USA.
Hojjat SalmasianDepartment of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.ORCID 0000-0002-9004-7149
Clyde B SchechterDepartment of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, New York, USA.
Noémie ElhadadDepartment of Biomedical Informatics, Columbia University, New York, New York, USA.
Joshua WeintraubDepartment of Radiology, Columbia University, New York, New York, USA.
Jason S AdelmanDepartment of Medicine, Columbia University Irving Medical Center, New York, New York, USA jsa2163@cumc.columbia.edu.ORCID 0000-0002-7497-257X

Funding

Patient Safety and Health Services Research TrainingT32HS026121 · AHRQ · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ADELMAN, JASON STUART, BARR, R GRAHAM · 2018 to 2024
$2.4M
AHRQ HHS T32 HS026121
6 · The paper itself

Abstract

Studying near-miss errors is essential to preventing errors from reaching patients. When an error is committed, it may be intercepted (near-miss) or it will reach the patient; estimates of the proportion that reach the patient vary widely. To better understand this relationship, we conducted a retrospective cohort study using two objective measures to identify wrong-patient imaging order errors involving radiation, estimating the proportion of errors that are intercepted and those that reach the patient. This study was conducted at a large integrated healthcare system using data from 1 January to 31 December 2019. The study used two outcome measures of wrong-patient orders: (1) wrong-patient orders that led to misadministration of radiation reported to the New York Patient Occurrence Reporting and Tracking System (NYPORTS) (misadministration events); and (2) wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder (RAR) measure, a measure identifying orders placed for a patient, retracted and rapidly reordered by the same clinician on a different patient (near-miss events). All imaging orders that involved radiation were extracted retrospectively from the healthcare system data warehouse. Among 293 039 total eligible orders, 151 were wrong-patient orders (3 misadministration events, 148 near-miss events), for an overall rate of 51.5 per 100 000 imaging orders involving radiation placed on the wrong patient. Of all wrong-patient imaging order errors, 2% reached the patient, translating to 50 near-miss events for every 1 error that reached the patient. This proportion provides a more accurate and reliable estimate and reinforces the utility of systematic measure of near-miss errors as an outcome for preventative interventions.

Indexed as

Delivery of Health Care, IntegratedHumansNew YorkRetrospective StudiesAdverse events, epidemiology and detectionMedical error, measurement/epidemiologyNear miss

Identifiers

PMID38071526
PMCPMC10872565

What OpenQuestion holds

Textmetadata
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.