Evidence map›Paper›PMID 33036897›Full record

ArticleAcademic radiology2021

Radiology Workload Changes During the COVID-19 Pandemic: Implications for Staff Redeployment.

Junzi Shi, Catherine S Giess, Tyler Martin, Karen A Lemaire, Patrick J Curley, Camden Bay, William W Mayo-Smith, Giles W Boland, Ramin Khorasani

Abstract read
In one paragraph

Article in Academic radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
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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

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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  4. Evaluating the impact of COVID-19 on DXA waiting lists and osteoporosis prescription trends in England 2019-2023.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
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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

9 authors.

Junzi ShiBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115; Harvard Medical School, Boston, Massachusetts. Electronic address: jshi9@bwh.harvard.edu.
Catherine S GiessBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115; Harvard Medical School, Boston, Massachusetts.
Tyler MartinBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115.
Karen A LemaireBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115.
Patrick J CurleyBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115.
Camden BayBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115.
William W Mayo-SmithBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115; Harvard Medical School, Boston, Massachusetts.
Giles W BolandBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115; Harvard Medical School, Boston, Massachusetts.
Ramin KhorasaniBrigham and Women's Hospital, Department of Radiology, 75 Francis St, Boston, MA 02115; Harvard Medical School, Boston, Massachusetts.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RATIONALE AND

objectivesQuantify changes in total and by-subspecialty radiology workload due to deferring nonurgent services during the initial COVID-19 pandemic, and describe operational strategies implemented due to shifts in priority. MATERIALS AND

methodsThis retrospective, Institutional Review Board-exempt, study was performed between February 3, 2020 and April 19, 2020 at a large academic medical center. During March 9-15 (intervention period), nonurgent outpatient service deferments began. Five-week periods pre- (baseline) and postintervention (COVID) were defined. Primary outcomes were radiology volume (reports per day) overall and in 11 subspecialty divisions. Linear regression assessed relationship between baseline vs. COVID volumes stratified by division. Secondary outcomes included changes in relative value units (RVUs), inpatient and outpatient volumes.

resultsThere were 62,791 baseline reports vs. 23,369 during COVID; a 60% overall precipitous volume decrease (p < 0.001). Mean volume decrease pre- and during-COVID was significant (p < 0.001) amongst all individual divisions. Mean volume decrease differed amongst divisions: Interventional Radiology experienced least disruption (29% volume decrease), 7 divisions experienced 40%-60% decreases, and Musculoskeletal, Breast, and Cardiovascular imaging experienced >75% volume decrease. Total RVUs decreased 60% (71,186 baseline; 28,476 COVID). Both outpatient and inpatient report volumes decreased; 72% (41,115 baseline; 11,326 COVID) and 43% (12,626 baseline vs. 6,845 COVID), respectively. In labor pool tracking data, 21.8% (162/744) total radiology employees were reassigned to other hospital duties during the intervention period.

conclusionPrecipitous radiology workload reductions impacted subspecialty divisions with marked variation. Data-driven operational decisions during COVID-19 assisted workflow and staffing assignment changes. Ongoing adjustments will be needed as healthcare systems transition operations to a "new normal."

Indexed as

BetacoronavirusCoronavirus InfectionsCOVID-19Pneumonia, ViralRadiologyHumansPandemicsRetrospective StudiesSARS-CoV-2WorkloadCOVID-19OperationsReassignmentStaffingVolume

Identifiers

PMID33036897
PMCPMC7531432

What OpenQuestion holds

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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.