Evidence map›Paper›PMID 35101869›Full record

ArticleBMJ open quality2022

System approach to prevent lost studies and improve radiology report turnaround time.

Jacob Schick, Jonelle M Petscavage-Thomas

Abstract read
In one paragraph

Article in BMJ open quality, 2022. 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

2 authors.

Jacob SchickPenn State College of Medicine, Hershey, Pennsylvania, USA.
Jonelle M Petscavage-ThomasRadiology, Penn State Health Milton S Hershey Medical Center, Hershey, Pennsylvania, USA jopa905@gmail.com.ORCID 0000-0001-6517-9732

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOn our picture archiving and communication system worklist, there was no way to differentiate body imaging (BI) from musculoskeletal (MSK) MR pelvis examinations. They were listed on only the BI worklist. This resulted in 'lost' MSK MR pelvis studies with high report turnaround time (TAT). Some exams had preliminary reports with substantiative changes made days later when found. The goals of this project were to create a solution to prevent 'lost' exams and improve TAT.

methodsA report of 3 months of MR pelvis studies was reviewed to determine time to first view by MSK radiologists, time of completion, time of preliminary report and time of final signature. Mean TAT was calculated and exams with delays in reporting resident misinterpretation recorded.An MSK reserve flag was created for the BI radiologists to use when they found an MSK study on their worklist. The flag moved them onto the MSK reserve worklist. A second intervention included technologists placing the reserve on examination completion. After this, another 3 months of data was analysed.

resultsThere was a significant improvement (p=0.0018) in time to view by MSK from preintervention mean of 1125 min (n=107) to postintervention mean of 526 min (n=127). There was also a significant improvement (p=0.0033) in time to view inpatient and Emergency department cases from 927 min to 357 min. Time from study completion to final signature also improved from a mean of 1764 min to 838 min, though not statistically significant (p=0.08). There were five cases of delay in reporting resident misinterpretation preintervention and none postintervention.

conclusionOur intervention shows the importance of modifying human and informatics factors to solve a patient safety issue.

introduction

Indexed as

RadiologyRadiology Information SystemsEmergency Service, HospitalHumansResearch Reportcommunicationhealthcare quality improvementinformation technology

Identifiers

PMID35101869
PMCPMC8804704

What OpenQuestion holds

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LicenceCC BY-NC
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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.