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Ghoshal S, Stovall N, King AH, Miller AS, Harris MB, Succi MD. Orthopedic Surgery Volume Trends During the COVID-19 Pandemic and Postvaccination Era: Implications for Healthcare Planning. J Arthroplasty 2024; 39:1959-1966.e1. [PMID: 38513749 DOI: 10.1016/j.arth.2024.03.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 03/10/2024] [Accepted: 03/12/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND The Coronavirus Disease 2019 (COVID-19) pandemic decreased surgical volumes, but prior studies have not investigated recovery through 2022, or analyzed specific procedures or cases of urgency within orthopedic surgery. The aims of this study were to (1) quantify the declines in orthopedic surgery volume during and after the pandemic peak, (2) characterize surgical volume recovery during the postvaccination period, and (3) characterize recovery in the 1-year postvaccine release period. METHODS We conducted a retrospective cohort study of 27,476 orthopedic surgeries from January 2019 to December 2022 at one urban academic quaternary referral center. We reported trends over the following periods: baseline pre-COVID-19 period (1/6/2019 to 1/4/2020), COVID-19 peak (3/15/2020 to 5/16/2020), post-COVID-19 peak (5/17/2020 to 1/2/2021), postvaccine release (1/3/2021 to 1/1/2022), and 1-year postvaccine release (1/2/2022 to 12/30/2022). Comparisons were performed with 2 sample t-tests. RESULTS Pre-COVID-19 surgical volume fell by 72% at the COVID-19 peak, especially impacting elective procedures (P < .001) and both hip and knee joint arthroplasty (P < .001) procedures. Nonurgent (P = .024) and urgent or emergency (P = .002) cases also significantly decreased. Postpeak recovery before the vaccine saw volumes rise to 92% of baseline, which further rose to 96% and 94% in 2021 and 2022, respectively. While elective procedures surpassed the baseline in 2022, nonurgent and urgent or emergency surgeries remained low. CONCLUSIONS The COVID-19 pandemic substantially reduced orthopedic surgical volumes, which have still not fully recovered through 2022, particularly nonelective procedures. The differential recovery within an orthopedic surgery program may result in increased morbidity and can serve to inform department-level operational recovery.
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Affiliation(s)
- Soham Ghoshal
- Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Nasir Stovall
- Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Alexander H King
- Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Amitai S Miller
- Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Mitchel B Harris
- Harvard Medical School, Boston, Massachusetts; Department of Orthopedic Surgery, Massachusetts General Hospital, Boston, Massachusetts
| | - Marc D Succi
- Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
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2
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Cheng D, Ghoshal S, Zattra O, Flash M, Lang M, Liu R, Lev MH, Hirsch JA, Saini S, Gee MS, Succi MD. Trends in oncological imaging during the COVID-19 pandemic through the vaccination era. Cancer Med 2023; 12:9902-9911. [PMID: 36775966 PMCID: PMC10166903 DOI: 10.1002/cam4.5678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/22/2023] [Accepted: 01/31/2023] [Indexed: 02/14/2023] Open
Abstract
BACKGROUND This study examines the impact that the COVID-19 pandemic has had on computed tomography (CT)-based oncologic imaging utilization. METHODS We retrospectively analyzed cancer-related CT scans during four time periods: pre-COVID (1/5/20-3/14/20), COVID peak (3/15/20-5/2/20), post-COVID peak (5/3/20-12/19/20), and vaccination period (12/20/20-10/30/21). We analyzed CTs by imaging indication, setting, and hospital type. Using percentage decrease computation and Student's t-test, we calculated the change in mean number of weekly cancer-related CTs for all periods compared to the baseline pre-COVID period. This study was performed at a single academic medical center and three affiliated hospitals. RESULTS During the COVID peak, mean CTs decreased (-43.0%, p < 0.001), with CTs for (1) cancer screening, (2) initial workup, (3) cancer follow-up, and (4) scheduled surveillance of previously treated cancer dropping by 81.8%, 56.3%, 31.7%, and 45.8%, respectively (p < 0.001). During the post-COVID peak period, cancer screenings and initial workup CTs did not return to prepandemic imaging volumes (-11.4%, p = 0.028; -20.9%, p = 0.024). The ED saw increases in weekly CTs compared to prepandemic levels (+31.9%, p = 0.008), driven by increases in cancer follow-up CTs (+56.3%, p < 0.001). In the vaccination period, cancer screening CTs did not recover to baseline (-13.5%, p = 0.002) and initial cancer workup CTs doubled (+100.0%, p < 0.001). The ED experienced increased cancer-related CTs (+75.9%, p < 0.001), driven by cancer follow-up CTs (+143.2%, p < 0.001) and initial workups (+46.9%, p = 0.007). CONCLUSIONS AND RELEVANCE The pandemic continues to impact cancer care. We observed significant declines in cancer screening CTs through the end of 2021. Concurrently, we observed a 2× increase in initial cancer workup CTs and a 2.4× increase in cancer follow-up CTs in the ED during the vaccination period, suggesting a boom of new cancers and more cancer examinations associated with emergency level acute care.
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Affiliation(s)
- Debby Cheng
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Soham Ghoshal
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Ottavia Zattra
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Moses Flash
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Min Lang
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Raymond Liu
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael H Lev
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Joshua A Hirsch
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sanjay Saini
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael S Gee
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Marc D Succi
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts, USA
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3
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Chan A, Flash MJ, Guo T, Zattra O, Boms O, Succi MD, Hirsch JA. Trends in Academic Productivity Among Radiologists During the COVID-19 Pandemic. J Am Coll Radiol 2023; 20:276-281. [PMID: 36496090 PMCID: PMC9729584 DOI: 10.1016/j.jacr.2022.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/21/2022] [Accepted: 10/03/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE There is a scarcity of literature examining changes in radiologist research productivity during the COVID-19 pandemic. The current study aimed to investigate changes in academic productivity as measured by publication volume before and during the COVID-19 pandemic. METHODS This single-center, retrospective cohort study included the publication data of 216 researchers consisting of associate professors, assistant professors, and professors of radiology. Wilcoxon's signed-rank test was used to identify changes in publication volume between the 1-year-long defined prepandemic period (publications between May 1, 2019, and April 30, 2020) and COVID-19 pandemic period (May 1, 2020, to April 30, 2021). RESULTS There was a significantly increased mean annual volume of publications in the pandemic period (5.98, SD = 7.28) compared with the prepandemic period (4.98, SD = 5.53) (z = -2.819, P = .005). Subset analysis demonstrated a similar (17.4%) increase in publication volume for male researchers when comparing the mean annual prepandemic publications (5.10, SD = 5.79) compared with the pandemic period (5.99, SD = 7.60) (z = -2.369, P = .018). No statistically significant changes were found in similar analyses with the female subset. DISCUSSION Significant increases in radiologist publication volume were found during the COVID-19 pandemic compared with the year before. Changes may reflect an overall increase in academic productivity in response to clinical and imaging volume ramp down.
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Affiliation(s)
- Alex Chan
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Faculty of Medicine, McMaster University, Hamilton, Ontario, Canada; and Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Moses J.E. Flash
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; and Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Teddy Guo
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Faculty of Medicine, McMaster University, Hamilton, Ontario, Canada; and Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Ottavia Zattra
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; and Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Okechi Boms
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; and Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Marc D. Succi
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Associate Chair, Innovation and Commercialization, Mass General Brigham Enterprise Radiology; and Member, ACR Economics Committee,Corresponding authors and reprints: Marc D. Succi, MD, Massachusetts General Hospital, Department of Radiology, 55 Fruit Street, Boston, MA 02114
| | - Joshua A. Hirsch
- Medically Engineered Solutions in Healthcare Incubator, Innovations in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Vice Chair Procedural Services, Director Interventional Neuroradiology, Chief Interventional Spine, Associate Department Quality Chair at Massachusetts General Hospital; Councilor to the ACR for Society of NeuroInterventional Surgery; Chair, Future Trends and Academic Committees ACR; Deputy Editor; JNIS; and Senior Affiliate Research Fellow, Neiman Health Policy Institute Joint Grant Program,Joshua A. Hirsch, MD, Massachusetts General Hospital, Department of Radiology, 55 Fruit Street, Boston, MA 02114
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Ho ML, Arnold CW, Decker SJ, Hazle JD, Krupinski EA, Mankoff DA. Institutional Strategies to Maintain and Grow Imaging Research During the COVID-19 Pandemic. Acad Radiol 2023; 30:631-639. [PMID: 36764883 PMCID: PMC9816088 DOI: 10.1016/j.acra.2022.12.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/23/2022] [Accepted: 12/24/2022] [Indexed: 01/09/2023]
Abstract
Understanding imaging research experiences, challenges, and strategies for academic radiology departments during and after COVID-19 is critical to prepare for future disruptive events. We summarize key insights and programmatic initiatives at major academic hospitals across the world, based on literature review and meetings of the Radiological Society of North America Vice Chairs of Research (RSNA VCR) group. Through expert discussion and case studies, we provide suggested guidelines to maintain and grow radiology research in the postpandemic era.
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Affiliation(s)
- Mai-Lan Ho
- Nationwide Children's Hospital and The Ohio State University, Columbus, Ohio.
| | | | | | - John D. Hazle
- The University of Texas MD Anderson Cancer Center, Houston, Texas
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5
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Ghoshal S, Rigney G, Cheng D, Brumit R, Gee MS, Hodin RA, Lillemoe KD, Levine WC, Succi MD. Institutional Surgical Response and Associated Volume Trends Throughout the COVID-19 Pandemic and Postvaccination Recovery Period. JAMA Netw Open 2022; 5:e2227443. [PMID: 35980636 PMCID: PMC9389350 DOI: 10.1001/jamanetworkopen.2022.27443] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 07/01/2022] [Indexed: 11/14/2022] Open
Abstract
Importance The COVID-19 pandemic is associated with decreased surgical procedure volumes, but existing studies have not investigated this association beyond the end of 2020, analyzed changes during the post-vaccine release period, or quantified these changes by patient acuity. Objective To quantify changes in the volume of surgical procedures at a 1017-bed academic quaternary care center from January 6, 2019, to December 31, 2021. Design, Setting, and Participants In this cohort study, 129 596 surgical procedure volumes were retrospectively analyzed during 4 periods: pre-COVID-19 (January 6, 2019, to January 4, 2020), COVID-19 peak (March 15, 2020, to May 2, 2020), post-COVID-19 peak (May 3, 2020, to January 2, 2021), and post-vaccine release (January 3, 2021, to December 31, 2021). Surgery volumes were analyzed by subspecialty and case class (elective, emergent, nonurgent, urgent). Statistical analysis was by autoregressive integrated moving average modeling. Main Outcomes and Measures The primary outcome of this study was the change in weekly surgical procedure volume across the 4 COVID-19 periods. Results A total of 129 596 records of surgical procedures were reviewed. During the COVID-19 peak, overall weekly surgical procedure volumes (mean [SD] procedures per week, 406.00 [171.45]; 95% CI, 234.56-577.46) declined 44.6% from pre-COVID-19 levels (mean [SD] procedures per week, 732.37 [12.70]; 95% CI, 719.67-745.08; P < .001). This weekly volume decrease occurred across all surgical subspecialties. During the post-COVID peak period, overall weekly surgical volumes (mean [SD] procedures per week, 624.31 [142.45]; 95% CI, 481.85-766.76) recovered to only 85.8% of pre-COVID peak volumes (P < .001). This insufficient recovery was inconsistent across subspecialties and case classes. During the post-vaccine release period, although some subspecialties experienced recovery to pre-COVID-19 volumes, others continued to experience declines. Conclusions and Relevance This quaternary care institution effectively responded to the pressures of the COVID-19 pandemic by substantially decreasing surgical procedure volumes during the peak of the pandemic. However, overall surgical procedure volumes did not fully recover to pre-COVID-19 levels well into 2021, with inconsistent recovery rates across subspecialties and case classes. These declines suggest that delays in surgical procedures may result in potentially higher morbidity rates in the future. The differential recovery rates across subspecialties may inform institutional focus for future operational recovery.
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Affiliation(s)
- Soham Ghoshal
- Harvard Medical School, Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center, Massachusetts General Hospital, Boston
| | - Grant Rigney
- Harvard Medical School, Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center, Massachusetts General Hospital, Boston
| | - Debby Cheng
- Harvard Medical School, Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center, Massachusetts General Hospital, Boston
| | - Ryan Brumit
- Department of Anesthesia, Massachusetts General Hospital Boston
| | - Michael S. Gee
- Harvard Medical School, Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center, Massachusetts General Hospital, Boston
- Department of Radiology, Massachusetts General Hospital, Boston
| | - Richard A. Hodin
- Harvard Medical School, Boston, Massachusetts
- Department of Surgery, Massachusetts General Hospital, Boston
| | - Keith D. Lillemoe
- Harvard Medical School, Boston, Massachusetts
- Department of Surgery, Massachusetts General Hospital, Boston
| | - Wilton C. Levine
- Harvard Medical School, Boston, Massachusetts
- Department of Anesthesia, Massachusetts General Hospital Boston
| | - Marc D. Succi
- Harvard Medical School, Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center, Massachusetts General Hospital, Boston
- Department of Radiology, Massachusetts General Hospital, Boston
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6
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Xu L, Herrington J, Cahill K, Risacher S, Gee MS. Strategies to optimize a pediatric magnetic resonance imaging service. Pediatr Radiol 2022; 52:152-157. [PMID: 33856504 PMCID: PMC8047568 DOI: 10.1007/s00247-021-05059-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 01/29/2021] [Accepted: 03/16/2021] [Indexed: 11/29/2022]
Abstract
A pediatric MRI service is a vital component of a successful radiology department. Building an efficient and effective pediatric MRI service is a multifaceted process that requires detailed planning for considerations related to finance, operations, quality and safety, and process improvement. These are compounded by the unique challenges of caring for pediatric patients, particularly in the setting of the recent coronavirus disease 2019 (COVID-19) pandemic. In addition to material resources, a successful pediatric MRI service depends on a collaborative team consisting of radiologists, physicists, technologists, nurses and vendor specialists, among others, to identify and resolve challenges and to strive for continued improvement. This article provides an overview of the factors involved in both starting and optimizing a pediatric MRI service, including commonly encountered obstacles and some proposed solutions to address them.
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Affiliation(s)
- Limin Xu
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St., Ellison 237, Boston, MA, 02114, USA
| | - Jeremy Herrington
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St., Ellison 237, Boston, MA, 02114, USA
| | - Kellie Cahill
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St., Ellison 237, Boston, MA, 02114, USA
| | - Seretha Risacher
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St., Ellison 237, Boston, MA, 02114, USA
| | - Michael S Gee
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St., Ellison 237, Boston, MA, 02114, USA.
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Schwertner A, McMenamy J, Naeger DM. Radiology Imaging Volume Changes During Discrete COVID-19 Pandemic Waves: Implications for the Delta Variant of Coronavirus and Future Pandemics. J Am Coll Radiol 2021; 19:415-422. [PMID: 34883068 PMCID: PMC8608677 DOI: 10.1016/j.jacr.2021.09.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 09/08/2021] [Indexed: 11/24/2022]
Abstract
Purpose The aim of this study was to evaluate radiology imaging volumes at distinct time periods throughout the coronavirus disease 2019 (COVID-19) pandemic as a function of regional COVID-19 hospitalizations. Methods Radiology imaging volumes and statewide COVID-19 hospitalizations were collected, and four 28-day time periods throughout the COVID-19 pandemic of 2020 were analyzed: pre–COVID-19 in January, the “first wave” of COVID-19 hospitalizations in April, the “recovery” time period in the summer of 2020 with a relative nadir of COVID-19 hospitalizations, and the “third wave” of COVID-19 hospitalizations in November. Imaging studies were categorized as inpatient, outpatient, or emergency department on the basis of patient location at the time of acquisition. A Mann-Whitney U test was performed to compare daily imaging volumes during each discrete 28-day time period. Results Imaging volumes overall during the first wave of COVID-19 infections were 55% (11,098/20,011; P < .001) of pre–COVID-19 imaging volumes. Overall imaging volumes returned during the recovery time period to 99% (19,915/20,011; P = .725), and third-wave imaging volumes compared with the pre–COVID-19 period were significantly lower in the emergency department at 88.8% (7,951/8,955; P < .001), significantly higher for outpatients at 115.7% (8,818/7,621; P = .008), not significantly different for inpatients at 106% (3,650/3,435; P = .053), and overall unchanged when aggregated together at 102% (20,419/20,011; P = .629). Conclusions Medical imaging rebounded after the first wave of COVID-19 hospitalizations, with relative stability of utilization over the ensuing phases of the pandemic. As widespread COVID-19 vaccination continues to occur, future surges in COVID-19 hospitalizations will likely have a negligible impact on imaging utilization.
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Affiliation(s)
- Adam Schwertner
- Department of Radiology, Denver Health Medical Center, Denver, Colorado; Department of Radiology, University of Colorado School of Medicine, Aurora, Colorado.
| | - John McMenamy
- Department of Radiology, Denver Health Medical Center, Denver, Colorado; Department of Radiology, University of Colorado School of Medicine, Aurora, Colorado
| | - David M Naeger
- Department of Radiology, Denver Health Medical Center, Denver, Colorado; Department of Radiology, University of Colorado School of Medicine, Aurora, Colorado
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Ranschaert E, Topff L, Pianykh O. Optimization of Radiology Workflow with Artificial Intelligence. Radiol Clin North Am 2021; 59:955-966. [PMID: 34689880 DOI: 10.1016/j.rcl.2021.06.006] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
The potential of artificial intelligence (AI) in radiology goes far beyond image analysis. AI can be used to optimize all steps of the radiology workflow by supporting a variety of nondiagnostic tasks, including order entry support, patient scheduling, resource allocation, and improving the radiologist's workflow. This article discusses several principal directions of using AI algorithms to improve radiological operations and workflow management, with the intention of providing a broader understanding of the value of applying AI in the radiology department.
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Affiliation(s)
- Erik Ranschaert
- Elisabeth-Tweesteden Hospital, Hilvarenbeekseweg 60, 5022 GC Tilburg, The Netherlands; Ghent University, C. Heymanslaan 10, 9000 Gent, Belgium.
| | - Laurens Topff
- Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Oleg Pianykh
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 25 New Chardon Street, Suite 470, Boston, MA 02114, USA
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9
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Surasi DSS, Wang X, Bathala TK, Hwang H, Arora S, Westphalen AC, Chang SD, Turkbey B. The impact and collateral damage of COVID-19 on prostate MRI and guided biopsy operations: Society of Abdominal Radiology Prostate Cancer Disease-Focused Panel survey analysis. Abdom Radiol (NY) 2021; 46:4362-4369. [PMID: 33904992 PMCID: PMC8077193 DOI: 10.1007/s00261-021-03087-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/03/2021] [Accepted: 04/09/2021] [Indexed: 11/30/2022]
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic has significantly affected health care systems throughout the world. A Qualtrics survey was targeted for radiologists around the world to study its effect on the operations of prostate MRI studies and biopsies. Descriptive statistics were reported. A total of 60 complete responses from five continents were included in the analysis. 70% of the responses were from academic institutions. Among all participants, the median (range) number of prostate MRI was 20 (0, 135) per week before the COVID-19 pandemic versus 10 (0, 30) during the lockdown period; the median (range) number of prostate biopsies was 4.5 (0, 60) per week before the COVID-19 versus 0 (0, 12) during the lockdown period. Among the 30% who used bowel preparation for their patients prior to MRI routinely, 11% stopped the bowel preparation due to the pandemic. 47% reported that their radiology departments faced staff disruptions, while 68% reported changes in clinic schedules in other clinical departments, particularly urology, genitourinary medical oncology, and radiation oncology. Finally, COVID-19 pandemic was found to disrupt not only the clinical prostate MRI operations but also impacted prostate MRI/biopsy research in up to 50% of institutions. The impact of this collateral damage in delaying diagnosis and treatment of prostate cancer is yet to be explored.
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Affiliation(s)
- Devaki Shilpa S Surasi
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA.
| | - Xuemei Wang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tharakeswara K Bathala
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Hyunsoo Hwang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sandeep Arora
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Antonio C Westphalen
- Departments of Radiology, Urology and Radiation Oncology, University of Washington, Seattle, WA, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Silvia D Chang
- Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, Canada
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Baris Turkbey
- Department Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
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10
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Naidich JJ, Boltyenkov A, Wang JJ, Cruzen E, Chusid J, Rula E, Sanelli PC. Recovery of outpatient imaging utilization during the first wave of the COVID-19 pandemic. Clin Imaging 2021; 80:277-282. [PMID: 34425546 PMCID: PMC8349737 DOI: 10.1016/j.clinimag.2021.07.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/09/2021] [Accepted: 07/27/2021] [Indexed: 11/16/2022]
Abstract
Objective During the COVID-19 pandemic, Radiology practices experienced marked reductions in outpatient imaging volumes. Our purpose was to evaluate the timing, rate, and degree of recovery of outpatient imaging during the first wave of the pandemic. We also sought to ascertain the relationship of outpatient imaging recovery to the incidence of COVID-19 cases. Methods Retrospective study of outpatient imaging volumes in a large healthcare system was performed from January 1, 2019-August 25, 2020. Dataset was split to compare Pre-COVID (weeks 1–9), Peak-COVID (weeks 10–15) and Recovery-COVID (weeks 16–34) periods. Chi-square and Independent-samples t-tests compared weekly outpatient imaging volumes in 2020 and 2019. Regression analyses assessed the rate of decline and recovery in Peak-COVID and Recovery-COVID periods, respectively. Results Total outpatient imaging volume in 2020 (weeks 1–34) was 327,738 exams, compared to 440,314 in 2019. The 2020 mean weekly imaging volumes were significantly decreased in Peak-COVID (p = 0.0148) and Recovery-COVID (p = 0.0003) periods. Mean weekly decline rate was −2580 exams/week and recovery rate was +617 exams/week. The 2020 Post-COVID (weeks 10–34) period had an average decrease of 36.5% (4813.4/13,178.6) imaging exams/week and total estimated decrease of 120,335 exams. Significant inverse correlation (−0.8338, p < 0.0001) was seen between positive-tested COVID-19 cases and imaging utilization with 1-week lag during Post-COVID (weeks 10–34) period. Conclusion Recovery of outpatient imaging volume during the first wave of COVID-19 pandemic showed a gradual return to pre-pandemic levels over the course of 3–4 months. The rate of imaging utilization was inversely associated with new positive-tested COVID-19 cases with a 1-week lag.
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Affiliation(s)
- Jason J Naidich
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States of America; Northwell Health, Manhasset, NY, United States of America.
| | - Artem Boltyenkov
- Siemens Medical Solutions USA, Inc., Malvern, PA, United States of America; Feinstein Institutes for Medical Research, Manhasset, NY, United States of America
| | - Jason J Wang
- Feinstein Institutes for Medical Research, Manhasset, NY, United States of America
| | - Eric Cruzen
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States of America; Northwell Health, Manhasset, NY, United States of America
| | - Jesse Chusid
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States of America; Northwell Health, Manhasset, NY, United States of America
| | - Elizabeth Rula
- Harvey L. Neiman Health Policy Institute, Reston, VA, United States of America
| | - Pina C Sanelli
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States of America; Northwell Health, Manhasset, NY, United States of America; Feinstein Institutes for Medical Research, Manhasset, NY, United States of America
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Automated tracking of emergency department abdominal CT findings during the COVID-19 pandemic using natural language processing. Am J Emerg Med 2021; 49:52-57. [PMID: 34062318 PMCID: PMC8154187 DOI: 10.1016/j.ajem.2021.05.057] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 05/08/2021] [Accepted: 05/18/2021] [Indexed: 02/06/2023] Open
Abstract
PURPOSE During the COVID-19 pandemic, emergency department (ED) volumes have fluctuated. We hypothesized that natural language processing (NLP) models could quantify changes in detection of acute abdominal pathology (acute appendicitis (AA), acute diverticulitis (AD), or bowel obstruction (BO)) on CT reports. METHODS This retrospective study included 22,182 radiology reports from CT abdomen/pelvis studies performed at an urban ED between January 1, 2018 to August 14, 2020. Using a subset of 2448 manually annotated reports, we trained random forest NLP models to classify the presence of AA, AD, and BO in report impressions. Performance was assessed using 5-fold cross validation. The NLP classifiers were then applied to all reports. RESULTS The NLP classifiers for AA, AD, and BO demonstrated cross-validation classification accuracies between 0.97 and 0.99 and F1-scores between 0.86 and 0.91. When applied to all CT reports, the estimated numbers of AA, AD, and BO cases decreased 43-57% in April 2020 (first regional peak of COVID-19 cases) compared to 2018-2019. However, the number of abdominal pathologies detected rebounded in May-July 2020, with increases above historical averages for AD. The proportions of CT studies with these pathologies did not significantly increase during the pandemic period. CONCLUSION Dramatic decreases in numbers of acute abdominal pathologies detected by ED CT studies were observed early on during the COVID-19 pandemic, though these numbers rapidly rebounded. The proportions of CT cases with these pathologies did not increase, which suggests patients deferred care during the first pandemic peak. NLP can help automatically track findings in ED radiology reporting.
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