Evidence map›Paper›PMID 33096163›Full record

ArticleRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology2020

A multi-institutional assessment of COVID-19-related risk in radiation oncology.

Natalie Viscariello, Suzanne Evans, Stephanie Parker, Deborah Schofield, Brett Miller, Stephen Gardner, Luis Fong de Los Santos, Christopher Hallemeier, Loucille Jordan, Edward Kim and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

11 authors.

Natalie ViscarielloUniversity of Washington, Seattle, USA. Electronic address: nvisc@uw.edu.
Suzanne EvansYale University, New Haven, USA.
Stephanie ParkerWake Forest Baptist Health, High Point, USA.
Deborah SchofieldAdventhealth Orlando, USA.
Brett MillerHenry Ford Healthcare System, Detroit, USA.
Stephen GardnerHenry Ford Healthcare System, Detroit, USA.
Luis Fong de Los SantosMayo Clinic, Rochester, USA.
Christopher HallemeierMayo Clinic, Rochester, USA.
Loucille JordanUniversity of Washington, Seattle, USA.
Edward KimUniversity of Washington, Seattle, USA.
Eric FordUniversity of Washington, Seattle, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe COVID-19 pandemic has presented challenges to delivering safe and timely care for cancer patients. The oncology community has undertaken substantial workflow adaptations to reduce transmission risk for patients and providers. While various control measureshave been proposed and implemented, little is known about their impact on safety of the radiation oncology workflow and potential for transmission. The objective of this study was to assess potential safety impacts of control measures employed during the COVID-19 pandemic.

methodsA multi-institutional study was undertaken to assess the risks of pandemic-associated workflow adaptations using failure mode and effects analysis (FMEA). Failure modes were identified and scored using FMEA formalism. FMEA scores were used to identify highest-risk aspects of the radiation therapy process. The impact of control measures on overall risk was quantified. Agreement among institutions was evaluated.

resultsThirty three failure modes and 22 control measures were identified. Control measures resulted in risk score reductions for 22 of the failure modes, with the largest reductions from screening of patients and staff, requiring use of masks, and regular cleaning of patient areas. The median risk score for all failure modes was reduced from 280 to 168. There was high institutional agreement for 90.3% of failure modes but only 47% of control measures.

conclusionsCOVID-related risks are similar across oncology practices in this study. While control measures can reducerisk, their use varied. The effectiveness of control measures on risk may guide selection of the highest-impact workflow adaptions to ensure safe care in oncology.

Indexed as

ComorbidityCOVID-19Cross InfectionHumansInfectious Disease Transmission, Patient-to-ProfessionalNeoplasmsPandemicsRadiation OncologyRiskRisk AssessmentRisk ManagementSARS-CoV-2WorkflowHealthcare failure mode and effect analysisPatient safetyRisk assessment

Identifiers

PMID33096163
PMCPMC7574842

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.