1
|
Vosshenrich J, Koerzdoerfer G, Fritz J. Modern acceleration in musculoskeletal MRI: applications, implications, and challenges. Skeletal Radiol 2024; 53:1799-1813. [PMID: 38441617 DOI: 10.1007/s00256-024-04634-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 08/09/2024]
Abstract
Magnetic resonance imaging (MRI) is crucial for accurately diagnosing a wide spectrum of musculoskeletal conditions due to its superior soft tissue contrast resolution. However, the long acquisition times of traditional two-dimensional (2D) and three-dimensional (3D) fast and turbo spin-echo (TSE) pulse sequences can limit patient access and comfort. Recent technical advancements have introduced acceleration techniques that significantly reduce MRI times for musculoskeletal examinations. Key acceleration methods include parallel imaging (PI), simultaneous multi-slice acquisition (SMS), and compressed sensing (CS), enabling up to eightfold faster scans while maintaining image quality, resolution, and safety standards. These innovations now allow for 3- to 6-fold accelerated clinical musculoskeletal MRI exams, reducing scan times to 4 to 6 min for joints and spine imaging. Evolving deep learning-based image reconstruction promises even faster scans without compromising quality. Current research indicates that combining acceleration techniques, deep learning image reconstruction, and superresolution algorithms will eventually facilitate tenfold accelerated musculoskeletal MRI in routine clinical practice. Such rapid MRI protocols can drastically reduce scan times by 80-90% compared to conventional methods. Implementing these rapid imaging protocols does impact workflow, indirect costs, and workload for MRI technologists and radiologists, which requires careful management. However, the shift from conventional to accelerated, deep learning-based MRI enhances the value of musculoskeletal MRI by improving patient access and comfort and promoting sustainable imaging practices. This article offers a comprehensive overview of the technical aspects, benefits, and challenges of modern accelerated musculoskeletal MRI, guiding radiologists and researchers in this evolving field.
Collapse
Affiliation(s)
- Jan Vosshenrich
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | | | - Jan Fritz
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.
| |
Collapse
|
2
|
Lee A, Lee E, Nair S, Wang CY, Chong J, Hallinan JTPD, Ang S. Reducing Delays in MRIs Under Sedation and General Anesthesia Using Quality Improvement Tools. J Am Coll Radiol 2024:S1546-1440(24)00527-1. [PMID: 38906500 DOI: 10.1016/j.jacr.2024.05.012] [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: 02/24/2024] [Revised: 05/18/2024] [Accepted: 05/21/2024] [Indexed: 06/23/2024]
Abstract
OBJECTIVE Develop structured, quality improvement interventions to achieve a 15%-point reduction in MRIs performed under sedation or general anesthesia (GA) delayed more than 15 min within a 6-month period. METHODS A prospective audit of MRIs under sedation or GA from January 2022 to June 2023 was conducted. A multidisciplinary team performed process mapping and root cause analysis for delays. Interventions were developed and implemented over four Plan, Do, Study, Act (PDSA) cycles, targeting workflow standardization, preadmission patient counseling, reinforcing adherence to scheduled scan times and written consent respectively. Delay times (compared with Kruskal-Wallis and Dunn's tests), delays more than 15 min and delays of 60 min or more at baseline and after each PDSA cycle were recorded. RESULTS In all, 627 MRIs under sedation or GA were analyzed, comprising 443 at baseline and 184 postimplementation. Of the 627, 556 (88.7%) scans were performed under sedation, 22 (3.5%) under monitored anesthesia care, and 49 (7.8%) under GA. At baseline, 71.6% (317 of 443) scans were delayed over 15 min and 28.2% (125 of 443) scans by 60 min or more, with a median delay of 30 min. Postimplementation, there was a 34.7%-point reduction in scans delayed more than 15 min, a 17.5%-point reduction in scans delayed by 60 min or more, and a reduction in median delay time by 15 min (P < .001). DISCUSSION Structured interventions significantly reduced delays in MRIs under sedation and GA, potentially improving outcomes for both patients and providers. Key factors included a diversity of perspectives in the study team, continued stakeholder engagement and structured quality improvement tools including PDSA cycles.
Collapse
Affiliation(s)
- Aric Lee
- Resident, Department of Diagnostic Imaging, National University Hospital, Singapore.
| | - Eunice Lee
- Associate Consultant, Department of Anaesthesia, National University Hospital, Singapore
| | - Shalini Nair
- Principal Radiographer and Deputy MRI In-charge, Department of Diagnostic Imaging, National University Hospital, Singapore
| | - Chi Yao Wang
- Senior Radiographer, Department of Diagnostic Imaging, National University Hospital, Singapore
| | - Jennifer Chong
- Senior Staff Nurse, Department of Diagnostic Imaging, National University Hospital, Singapore
| | - James Thomas Patrick Decourcy Hallinan
- Senior Consultant and Division Head, Musculoskeletal Imaging, Department of Diagnostic Imaging, and Assistant Professor, Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Sophia Ang
- Senior Consultant, Department of Anaesthesia, National University Hospital, Singapore; Vice Chairman (Quality, Safety & Operations), Medical Board, National University Hospital, Singapore
| |
Collapse
|
3
|
Lang M, Clifford B, Lo WC, Applewhite BP, Tabari A, Filho ALMG, Hosseini Z, Longo MGF, Cauley SF, Setsompop K, Bilgic B, Feiweier T, Lev MH, Schaefer PW, Rapalino O, Huang SY, Conklin J. Clinical Evaluation of a 2-Minute Ultrafast Brain MR Protocol for Evaluation of Acute Pathology in the Emergency and Inpatient Settings. AJNR Am J Neuroradiol 2024; 45:379-385. [PMID: 38453413 PMCID: PMC11288578 DOI: 10.3174/ajnr.a8143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/07/2023] [Indexed: 03/09/2024]
Abstract
BACKGROUND AND PURPOSE The use of MR imaging in emergency settings has been limited by availability, long scan times, and sensitivity to motion. This study assessed the diagnostic performance of an ultrafast brain MR imaging protocol for evaluation of acute intracranial pathology in the emergency department and inpatient settings. MATERIALS AND METHODS Sixty-six adult patients who underwent brain MR imaging in the emergency department and inpatient settings were included in the study. All patients underwent both the reference and the ultrafast brain MR protocols. Both brain MR imaging protocols consisted of T1-weighted, T2/T2*-weighted, FLAIR, and DWI sequences. The ultrafast MR images were reconstructed by using a machine-learning assisted framework. All images were reviewed by 2 blinded neuroradiologists. RESULTS The average acquisition time was 2.1 minutes for the ultrafast brain MR protocol and 10 minutes for the reference brain MR protocol. There was 98.5% agreement on the main clinical diagnosis between the 2 protocols. In head-to-head comparison, the reference protocol was preferred in terms of image noise and geometric distortion (P < .05 for both). The ultrafast ms-EPI protocol was preferred over the reference protocol in terms of reduced motion artifacts (P < .01). Overall diagnostic quality was not significantly different between the 2 protocols (P > .05). CONCLUSIONS The ultrafast brain MR imaging protocol provides high accuracy for evaluating acute pathology while only requiring a fraction of the scan time. Although there was greater image noise and geometric distortion on the ultrafast brain MR protocol images, there was significant reduction in motion artifacts with similar overall diagnostic quality between the 2 protocols.
Collapse
Affiliation(s)
- Min Lang
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Bryan Clifford
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
| | - Wei-Ching Lo
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
| | - Brooks P Applewhite
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Azadeh Tabari
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | | | - Zahra Hosseini
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
| | - Maria Gabriela Figueiro Longo
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Stephen F Cauley
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
- Harvard-MIT Health Sciences and Technology (S.F.C., B.B., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Kawin Setsompop
- Departments of Radiology and Electrical Engineering (K.S.), Stanford University, Stanford, California
| | - Berkin Bilgic
- Harvard-MIT Health Sciences and Technology (S.F.C., B.B., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | | | - Michael H Lev
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Pamela W Schaefer
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Otto Rapalino
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Susie Y Huang
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
- Harvard-MIT Health Sciences and Technology (S.F.C., B.B., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - John Conklin
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| |
Collapse
|
4
|
Petroianu LPG, Li L, Mieloszyk RJ, Mastrangelo CM, Stapleton S, Hall C. MRI log file analysis for workflow improvement. Curr Probl Diagn Radiol 2024; 53:192-200. [PMID: 37951726 DOI: 10.1067/j.cpradiol.2023.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/14/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023]
Abstract
Magnetic Resonance Imaging (MRI) is an important diagnostic scanning tool for the detection and monitoring of specific diseases and conditions. However, the equipment cost, maintenance and specialty training of the technologists make the examination expensive. Consequently, unnecessary scanner time caused by poor scheduling, repeated sequences, aborted sequences, scanner idleness, or capture of non-diagnostic or low-value sequences is an opportunity to reduce costs and increase efficiency. This paper analyzes data collected from log files on 29 scanners over several years. 'Wasted' time is defined and key performance indicators (KPIs) are identified. A decrease in exam duration results when actively modifying and monitoring the number of sequences that comprise the exam card for a protocol.
Collapse
Affiliation(s)
- Larissa P G Petroianu
- Industrial & Systems Engineering, University of Washington, Box 352650, Seattle, WA 98195, United States
| | - Lun Li
- Industrial & Systems Engineering, University of Washington, Box 352650, Seattle, WA 98195, United States
| | | | - Christina M Mastrangelo
- Industrial & Systems Engineering, University of Washington, Box 352650, Seattle, WA 98195, United States.
| | - Shawn Stapleton
- Philips Healthcare, Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Christopher Hall
- Philips Healthcare, Department of Radiology, University of Washington, Seattle, WA 98195, United States
| |
Collapse
|
5
|
Geng R, Buelo CJ, Sundaresan M, Starekova J, Panagiotopoulos N, Oechtering TH, Lawrence EM, Ignaciuk M, Reeder SB, Hernando D. Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation. J Magn Reson Imaging 2023; 58:429-441. [PMID: 36583550 PMCID: PMC10310884 DOI: 10.1002/jmri.28564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 11/17/2022] [Accepted: 11/18/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND There is an unmet need for fully automated image prescription of the liver to enable efficient, reproducible MRI. PURPOSE To develop and evaluate artificial intelligence (AI)-based liver image prescription. STUDY TYPE Prospective. POPULATION A total of 570 female/469 male patients (age: 56 ± 17 years) with 72%/8%/20% assigned randomly for training/validation/testing; two female/four male healthy volunteers (age: 31 ± 6 years). FIELD STRENGTH/SEQUENCE 1.5 T, 3.0 T; spin echo, gradient echo, bSSFP. ASSESSMENT A total of 1039 three-plane localizer acquisitions (26,929 slices) from consecutive clinical liver MRI examinations were retrieved retrospectively and annotated by six radiologists. The localizer images and manual annotations were used to train an object-detection convolutional neural network (YOLOv3) to detect multiple object classes (liver, torso, and arms) across localizer image orientations and to output corresponding 2D bounding boxes. Whole-liver image prescription in standard orientations was obtained based on these bounding boxes. 2D detection performance was evaluated on test datasets by calculating intersection over union (IoU) between manual and automated labeling. 3D prescription accuracy was calculated by measuring the boundary mismatch in each dimension and percentage of manual volume covered by AI prescription. The automated prescription was implemented on a 3 T MR system and evaluated prospectively on healthy volunteers. STATISTICAL TESTS Paired t-tests (threshold = 0.05) were conducted to evaluate significance of performance difference between trained networks. RESULTS In 208 testing datasets, the proposed method with full network had excellent agreement with manual annotations, with median IoU > 0.91 (interquartile range < 0.09) across all seven classes. The automated 3D prescription was accurate, with shifts <2.3 cm in superior/inferior dimension for 3D axial prescription for 99.5% of test datasets, comparable to radiologists' interreader reproducibility. The full network had significantly superior performance than the tiny network for 3D axial prescription in patients. Automated prescription performed well across single-shot fast spin-echo, gradient-echo, and balanced steady-state free-precession sequences in the prospective study. DATA CONCLUSION AI-based automated liver image prescription demonstrated promising performance across the patients, pathologies, and field strengths studied. EVIDENCE LEVEL 4. TECHNICAL EFFICACY Stage 1.
Collapse
Affiliation(s)
- Ruiqi Geng
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Collin J. Buelo
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Mahalakshmi Sundaresan
- Department of Electrical and Computer Engineering, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Jitka Starekova
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Nikolaos Panagiotopoulos
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Radiology and Nuclear Medicine, Universität zu Lübeck, Lübeck, Germany (Haus A, Ratzeburger Allee 160, 23562 Lübeck, Germany)
| | - Thekla H. Oechtering
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Radiology and Nuclear Medicine, Universität zu Lübeck, Lübeck, Germany (Haus A, Ratzeburger Allee 160, 23562 Lübeck, Germany)
| | - Edward M. Lawrence
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Marcin Ignaciuk
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Scott B. Reeder
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Medicine, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Emergency Medicine, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Electrical and Computer Engineering, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
- Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA (1111 Highland Ave, Madison, WI 53705)
| |
Collapse
|
6
|
Lang M, Rapalino O, Huang S, Lev MH, Conklin J, Wald LL. Emerging Techniques and Future Directions: Fast and Portable Magnetic Resonance Imaging. Magn Reson Imaging Clin N Am 2022; 30:565-582. [PMID: 35995480 DOI: 10.1016/j.mric.2022.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Fast MRI and portable MRI are emerging as promising technologies to improve the speed, efficiency, and availability of MR imaging. Fast MRI methods are increasingly being adopted to create screening protocols for the diagnosis and management of acute pathology in the emergency department. Faster imaging can facilitate timely diagnosis, reduce motion artifacts, and improve departmental MR operations. Point-of-care and portable MRI are emerging technologies that require radiologists to reenvision the role of MRI as a tool with greater accessibility, fewer siting constraints, and the ability to provide valuable diagnostic information at the bedside. Recently introduced commercially available pulse sequences and new MRI scanners are bringing these technologies closer to the patient's clinical setting, and we expect their use to only increase over the coming decade. This article provides an overview of these emerging technologies for emergency radiologists.
Collapse
Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Susie Huang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
| | - Lawrence L Wald
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
| |
Collapse
|
7
|
Mazzio E, Mistry RD, Rosenthal S, Ser E, Jewell J, Martin J, Messer R, Straley M, Leonard J, Press CA. Neuroimaging for Pediatric Non-First-Time Seizures in the Emergency Department. Neurol Clin Pract 2022; 12:e7-e13. [DOI: 10.1212/cpj.0000000000001165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 02/28/2022] [Indexed: 11/15/2022]
Abstract
AbstractBackground& Objectives: Neuroimaging is often part of the workup for a pediatric patient presenting with a seizure to an emergency department (ED). We aim to evaluate when neuroimaging in the emergency department for children with a non-first-time seizure, or non-index seizure (NIS), is associated with an acute change in management (ACM).Methods:Retrospective cohort study of all pediatric patients presenting to an ED from 2008-2018 with a NIS, excluding repeat febrile seizures, who underwent neuroimaging. Clinical characteristics were extracted from the electronic medical record. The primary outcome was new abnormal neuroimaging resulting in an ACM, defined as admission to the hospital, neurosurgical intervention, or new non-seizure medication administration.Results:We identified 492 encounters. Neuroimaging revealed new findings in 21% of encounters and led to ACMs in 5% of encounters. ACMs included admissions, neurosurgical interventions, and non-seizure medication changes. Factors associated with ACM included new seizure type (OR 3.3, 95% CI 1.3-8.0), new focal exam finding (OR 3.0, 95% CI 1.3-7.1), altered mental status (OR 2.9, 95% CI 1.2-7.0), and a history of only provoked seizures (OR 2.8, 95% CI 1.0-7.5). Patients with 2 risk factors had an OR 6.9 (95% CI 1.8 – 26.5) for an ACM, those with 3-4 risk factors had an OR of 45.8 (95% CI 9.8-213.2). The negative predictive value for ACM in a patient with no risk factors was 98.6% (95% CI 95.9 - 99.5).Discussion:Patients with a NIS who have abnormal neuroimaging associated with an ACM present with unique risk factors. Prospectively validating these factors may allow for a prediction tool for NIS in EDs where reduced exposure to ionizing radiation, sedation, and resource utilization is critically important.
Collapse
|
8
|
Sun J, Lv H, Li M, Zhao L, Liu Y, Zeng N, Wei X, Chen Q, Ren P, Liu Y, Zhang P, Yang Z, Zhang Z, Wang Z. How much abdominal fat do obese patients lose short term after laparoscopic sleeve gastrectomy? A quantitative study evaluated with MRI. Quant Imaging Med Surg 2021; 11:4569-4582. [PMID: 34737924 DOI: 10.21037/qims-20-1380] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 05/28/2021] [Indexed: 11/06/2022]
Abstract
Background This study aimed to elucidate the changes in the amount of abdominal adipose tissue after laparoscopic sleeve gastrectomy in obese Chinese patients over a relatively short follow-up period and to analyze the differences in the effects of surgery between genders. Methods Ninety-one patients were enrolled in the study, including 18 males and 73 females. These patients underwent laparoscopic sleeve gastrectomy between November 2017 and November 2019. Before and short term after surgery, the areas of subcutaneous/visceral adipose tissue and the liver proton density fat fraction were calculated with upper abdominal magnetic resonance (MR) examinations. Results Approximately 100 days after surgery, the median values of weight loss and body mass index reduction were 23.1 kg and 8.1 kg/m2, respectively. The patients achieved a greater absolute loss of subcutaneous adipose tissue index than of visceral adipose tissue index (3.2×10-3 vs. 1.6×10-3, P<0.001). The amount of weight loss, body mass index loss and absolute/relative reduction in visceral adipose tissue index were much greater in males than in females (31.7 vs. 21.7 kg, P<0.001; 9.8 vs. 7.9 kg/m2, P=0.016; 2.5×10-3 vs. 1.3×10-3, P=0.007; 28.2% vs. 20.9%, P=0.029). There was a correlation between decreased amounts in subcutaneous and visceral adipose tissue in sum and weight loss (r=0.282, P=0.032). The absolute/relative reduction in visceral adipose tissue index was also correlated with absolute/relative reduction in liver proton density fat fraction (r=0.283, P=0.013; r=0.372, P=0.001). Conclusions The reductions in body weight and visceral fat were more significant in male patients. The sum of absolute reduction in subcutaneous and visceral fat deposits was correlated with weight loss, in all patients enrolled. For severely obese patients, an upper abdominal MR examination could assess the body tissue composition and how it changes after bariatric surgery.
Collapse
Affiliation(s)
- Jing Sun
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Han Lv
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Mengyi Li
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University & National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Lei Zhao
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yawen Liu
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Na Zeng
- National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xuan Wei
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Pengling Ren
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yang Liu
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University & National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Peng Zhang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University & National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhongtao Zhang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University & National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
9
|
Meyl TP, Berghöfer A, Blatter T, Heverhagen JT, de Bucourt M, Maurer MH. Software-Based Evaluation of Optimization Potential for Clinical MRI Scanners in Radiology. ROFO-FORTSCHR RONTG 2021; 194:391-399. [PMID: 34687027 DOI: 10.1055/a-1659-8821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
OBJECTIVE The aim of the study was to use a software application to analyze the examination times and changeover times of two clinically highly applied MRI scanners at a university hospital for radiology and to evaluate whether this could result in optimization potential for examination planning in the daily clinical routine of MRI diagnostics. MATERIALS AND METHODS Based on the newly developed software application "Teamplay Usage" (Siemens Healthineers, Germany), the examinations carried out on two MRI scanners (1.5 T and 3 T) were investigated within an analysis period of 12 months with regard to the type of examination and its duration. In addition, compliance with the previously defined planning time (30, 45, 60 min.) was checked and deviations were analyzed. In addition, the changeover times between the examinations were determined and a possible influence due to the exchange of MRI coils was investigated for a selection of change combinations. RESULTS For the total of 7184 (1.5 T: 3740; 3 T: 3444) examinations included in the study, the median examination time was 43:02 minutes (1.5 T: 43:17 min.; 3 T: 42:45 min.). The ten most frequent types of examinations per MRI scanner were completed within the predefined plan time of 54.5 % (1.5 T) and 51.9 % (3 T), taking into account a previously defined preparation and post-processing time of 9 minutes per examination. Overall, more time was spent on examinations with a planned time of 30 minutes, whereas the majority of the examinations planned with 45 minutes were also completed within this time. Examinations with a planned time of 60 minutes usually took less time. A comparison between the planned time and the determined examination duration of the most common types of examinations showed overall a slight potential for optimization. Coil exchanges between two examinations had a small, but statistically not significant effect on the median changeover time (p = 0.062). CONCLUSION Utilizing a software-based analysis, a detailed overview of the type of examination, examination duration, and changeover times of frequently used clinical MRI scanners could be obtained. In the clinic examined, there was little potential for optimization of examination planning. An exchange of MRI coils necessary for different types of examination only had a small effect on the changeover times. KEY POINTS · The use of the "Teamplay Usage" software application enables a comprehensive overview of the type of examination, examination duration, and changeover times for MRI scanners.. · Adjustments to examination planning for MRI diagnostics show optimization potential, which, however, is to be assessed as low in the clinic examined.. · Necessary replacements of MRI coils only have a small effect on the changeover times.. CITATION FORMAT · Meyl TP, Berghöfer A, Blatter T et al. Software-Based Evaluation of Optimization Potential for Clinical MRI Scanners in Radiology. Fortschr Röntgenstr 2021; DOI: 10.1055/a-1659-8821.
Collapse
Affiliation(s)
- Tobias Philipp Meyl
- Medical Department, Medical Strategy, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Anne Berghöfer
- Institute for Social Medicine, Epidemiology, and Health Economics, Charité - Universitätsmedizin Berlin, Germany
| | - Tobias Blatter
- Institute for Clinical Chemnistry, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Johannes T Heverhagen
- Department for Diagnostic, Interventional, and Paediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Maximilian de Bucourt
- Clinic for Diagnostic and Interventional Radiology, Charité Universitätsmedizin Berlin, Germany
| | - Martin H Maurer
- Department for Diagnostic, Interventional, and Paediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| |
Collapse
|
10
|
Analysis of core processes of the MRI workflow for improved capacity utilization. Eur J Radiol 2021; 138:109648. [PMID: 33740625 DOI: 10.1016/j.ejrad.2021.109648] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 02/14/2021] [Accepted: 03/10/2021] [Indexed: 11/22/2022]
Abstract
PURPOSE To analyze core processes of the MRI workflow and to evaluate efficiency for improved patient throughput and capacity utilization. METHOD Prospective data collection was conducted during a four-week time period and a total sum of 160 working hours for each of the two 1.5 T MRI scanners. Three core processes defined the value stream of patient handling before, during and after the MRI examination: i) Scheduling & Registration, ii) Organization & Preparation, and iii) MR scan. Quantitative data was collected for six essential time intervals of the MRI workflow. RESULTS A total of 302 MRI examinations were assessed. The workflow analysis revealed that effective utilization of scan capacity during operating hours varied by scanner (Scanner 1: 77 % / Scanner 2: 85 %). Mean process times for were: patient preparation time 18.9 min (±15.1) p = 0.11, scan preparation time 5.7 min (±4.0) p = 0,015, effective scan time 39.6 min (±18.0) p < 0.0001, scan room occupation time 50.9 min (±21.0) p < 0.0001, clean-up time 5.6 min (±3.2) p = 0.001, total patient handling time 69.7 min (±26.3) p < 0.0001, turnover time 13.4 min (±21.4) p = 0.65. CONCLUSIONS This study demonstrates the utility and applicability of a standardized core processes analyses for MRI scanning, which identified underutilization of scanning capacities, related to multiple factors, such as punctuality of patients, the number of same day cancellations, the process of placing an IV access and patient transport contribute to underutilization of MRI scanners. Furthermore, proactive patient management and effective communication with patients and referring physicians might have relevant time saving potential in the scan room.
Collapse
|
11
|
Bor DS, Sharpe RE, Bode EK, Hunt K, Gozansky WS. Increasing Patient Access to MRI Examinations in an Integrated Multispecialty Practice. Radiographics 2021; 41:E1-E8. [PMID: 33411608 DOI: 10.1148/rg.2021200082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A multidisciplinary team evaluated and improved the MRI processes within the authors' integrated health care system, with the aim to increase patient access to MRI. The authors created a SMART (specific, measurable, achievable, relevant, and time-based) goal of decreasing the average number of days to wait for MRI examination by 50%, from 15 to 7.5 days, while also creating capacity to meet demand for same-day and next-day MRI appointment requests. The current performance metrics and processes were compared with available benchmarking and best practice data. Several work groups were created to empower and support frontline teams to identify and capture improvement opportunities. Across all MRI processes, teams focused on creating standard work, advancing practice to top of scope, removing waste, improving communication, reducing rework, and improving patient experience. Patient access to MRI was monitored, measured as the average number of days to wait from the time of scheduling to the MRI examination and time to the third-available appointment. The authors also monitored secondary outcomes (patient satisfaction, throughput metrics) and a balancing measure (technical repeat examination rates). The access improved after intervention: the average number of days to wait for MRI access decreased from 14.2 days to 5.8 days after the intervention (-8.4 days, -59.2%, P < .0001) and third-available appointment decreased from 18 days to 0 days. Ten to 20 same-day and next-day appointments became routinely available. The throughput metrics improved, and balancing measures were not changed. This project resulted in significant improvements in patient access to MRI examinations. The findings demonstrate the value of a multidisciplinary team applying comprehensive improvement strategies to increase patient access to complex services, such as MRI. ©RSNA, 2021.
Collapse
Affiliation(s)
- Daniel S Bor
- From the University of Colorado Denver, Denver, Colo (D.S.B); Department of Medical Imaging, Kaiser Permanente Colorado, Denver, Colo (D.S.B., K.H); Department of Medical Imaging (R.E.S., E.K.B.) and Departments of Internal Medicine and Geriatrics (W.S.G.), Colorado Permanente Medical Group, Denver, Colo; and Department of Radiology, Mayo Clinic, 5881 E Mayo Blvd, Phoenix, AZ 85054 (R.E.S.)
| | - Richard E Sharpe
- From the University of Colorado Denver, Denver, Colo (D.S.B); Department of Medical Imaging, Kaiser Permanente Colorado, Denver, Colo (D.S.B., K.H); Department of Medical Imaging (R.E.S., E.K.B.) and Departments of Internal Medicine and Geriatrics (W.S.G.), Colorado Permanente Medical Group, Denver, Colo; and Department of Radiology, Mayo Clinic, 5881 E Mayo Blvd, Phoenix, AZ 85054 (R.E.S.)
| | - Eric K Bode
- From the University of Colorado Denver, Denver, Colo (D.S.B); Department of Medical Imaging, Kaiser Permanente Colorado, Denver, Colo (D.S.B., K.H); Department of Medical Imaging (R.E.S., E.K.B.) and Departments of Internal Medicine and Geriatrics (W.S.G.), Colorado Permanente Medical Group, Denver, Colo; and Department of Radiology, Mayo Clinic, 5881 E Mayo Blvd, Phoenix, AZ 85054 (R.E.S.)
| | - Kandace Hunt
- From the University of Colorado Denver, Denver, Colo (D.S.B); Department of Medical Imaging, Kaiser Permanente Colorado, Denver, Colo (D.S.B., K.H); Department of Medical Imaging (R.E.S., E.K.B.) and Departments of Internal Medicine and Geriatrics (W.S.G.), Colorado Permanente Medical Group, Denver, Colo; and Department of Radiology, Mayo Clinic, 5881 E Mayo Blvd, Phoenix, AZ 85054 (R.E.S.)
| | - Wendolyn S Gozansky
- From the University of Colorado Denver, Denver, Colo (D.S.B); Department of Medical Imaging, Kaiser Permanente Colorado, Denver, Colo (D.S.B., K.H); Department of Medical Imaging (R.E.S., E.K.B.) and Departments of Internal Medicine and Geriatrics (W.S.G.), Colorado Permanente Medical Group, Denver, Colo; and Department of Radiology, Mayo Clinic, 5881 E Mayo Blvd, Phoenix, AZ 85054 (R.E.S.)
| |
Collapse
|
12
|
Drose JA, Pritchard NL, Honce JM, Snuttjer DK, Borgstede JP. Utilizing Process Improvement Methodology to Improve Inpatient Access to MRI. Radiographics 2019; 39:2103-2110. [PMID: 31697626 DOI: 10.1148/rg.2019190043] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Julia A Drose
- From the Department of Radiology, University of Colorado Health Sciences Center, University of Colorado Hospital, 12401 E 17th Ave, Mail Stop L954, Aurora, CO 80045
| | - Nancy L Pritchard
- From the Department of Radiology, University of Colorado Health Sciences Center, University of Colorado Hospital, 12401 E 17th Ave, Mail Stop L954, Aurora, CO 80045
| | - Justin M Honce
- From the Department of Radiology, University of Colorado Health Sciences Center, University of Colorado Hospital, 12401 E 17th Ave, Mail Stop L954, Aurora, CO 80045
| | - Denise K Snuttjer
- From the Department of Radiology, University of Colorado Health Sciences Center, University of Colorado Hospital, 12401 E 17th Ave, Mail Stop L954, Aurora, CO 80045
| | - James P Borgstede
- From the Department of Radiology, University of Colorado Health Sciences Center, University of Colorado Hospital, 12401 E 17th Ave, Mail Stop L954, Aurora, CO 80045
| |
Collapse
|
13
|
Canellas R, Rosenkrantz AB, Taouli B, Sala E, Saini S, Pedrosa I, Wang ZJ, Sahani DV. Abbreviated MRI Protocols for the Abdomen. Radiographics 2019; 39:744-758. [PMID: 30901285 DOI: 10.1148/rg.2019180123] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Technical advances in MRI have improved image quality and have led to expanding clinical indications for its use. However, long examination and interpretation times, as well as higher costs, still represent barriers to use of MRI. Abbreviated MRI protocols have emerged as an alternative to standard MRI protocols. These abbreviated MRI protocols seek to reduce longer MRI protocols by eliminating unnecessary or redundant sequences that negatively affect cost, MRI table time, patient comfort, image quality, and image interpretation time. However, the diagnostic information is generally not compromised. Abbreviated MRI protocols have already been used successfully for hepatocellular carcinoma screening, for prostate cancer detection, and for screening for nonalcoholic fatty liver disease as well as monitoring patients with this disease. It has been reported that image acquisition time and costs can be considerably reduced with abbreviated MRI protocols, compared with standard MRI protocols, while maintaining a similar sensitivity and accuracy. Nevertheless, multiple applications still need to be explored in the abdomen and pelvis (eg, surveillance of metastases to the liver; follow-up of cystic pancreatic lesions, adrenal incidentalomas, and small renal masses; evaluation of ovarian cysts in postmenopausal women; staging of cervical and uterine corpus neoplasms; evaluation of müllerian duct anomalies). This article describes some successful applications of abbreviated MRI protocols, demonstrates how they can help in improving the MRI workflow, and explores potential future directions. ©RSNA, 2019.
Collapse
Affiliation(s)
- Rodrigo Canellas
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Andrew B Rosenkrantz
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Bachir Taouli
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Evis Sala
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Sanjay Saini
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Ivan Pedrosa
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Zhen J Wang
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Dushyant V Sahani
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (R.C., S.S., D.V.S.); Department of Radiology, NYU Langone Health, New York, NY (A.B.R.); Department of Radiology, Mount Sinai Hospital, New York, NY (B.T.); Department of Radiology, University of Cambridge, Cambridge, England (E.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| |
Collapse
|
14
|
Optimizing MRI Logistics: Focused Process Improvements Can Increase Throughput in an Academic Radiology Department. AJR Am J Roentgenol 2017; 208:W38-W44. [DOI: 10.2214/ajr.16.16680] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
|
15
|
Wessman BV, Moriarity AK, Ametlli V, Kastan DJ. Reducing barriers to timely MR imaging scheduling. Radiographics 2015; 34:2064-70. [PMID: 25384302 DOI: 10.1148/rg.347140025] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Scheduling a magnetic resonance (MR) imaging study at the authors' large health system in 2011 required considerable preparation before an appointment time was given to a patient. Difficulties in promptly scheduling appointments resulted from the varying time required for examinations, depending on the requested protocol, availability of appropriate MR imaging equipment, examination timing, prior insurance authorization verification, and proper patient screening. These factors contributed to a backlog of patients to schedule that regularly exceeded 300. A multidisciplinary process-improvement team was assembled to improve the turnaround time for scheduling an outpatient MR imaging examination (the interval between the time when the order was received and the time when the patient was informed about the MR imaging appointment). Process improvements targeted by the team included protocol turnaround time, schedule standardization, schedule intervals, examination timing, service standards, and scheduling redesign. Using lean methods and multiple plan-do-check-act cycles, the time to schedule an outpatient MR imaging examination improved from 117 hours to 33 hours, a 72% reduction, during the 9-month study period in 2011-2012. The number of patients in the scheduling queue was reduced by 90%. Overall MR imaging examinations within the specific patient population studied increased from 773 patient studies during the first month of intervention to 1444 studies the following month and averaged over 1279 patient studies per month throughout the study.
Collapse
Affiliation(s)
- Brooke V Wessman
- From the Department of Diagnostic Radiology, Henry Ford Hospital, 2799 W Grand Blvd, Detroit, MI 48202
| | | | | | | |
Collapse
|
16
|
Van Schouwenburg F, Ackermann C, Pitcher R. An audit of elective outpatient magnetic resonance imaging in a tertiary South African public-sector hospital. SA J Radiol 2014. [DOI: 10.4102/sajr.v18i1.689] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
Background: Increasing demand for magnetic resonance imaging (MRI) has resulted in longer waiting times for elective MRI, particularly in resource-limited healthcare environments.However, inappropriate imaging requests may also contribute to prolonged MRI waiting times. At the time of the present study, the waiting time for elective MRI studies at Tygerberg Hospital (TBH), a tertiary-level public-sector healthcare facility in Cape Town (South Africa),was 24 weeks.Objectives: To document the nature and clinical appropriateness of scheduled TBH outpatient MRI examinations.Method: A retrospective analysis of the referral forms of all elective outpatient MRIexaminations scheduled at TBH from 01 June to 30 November 2011 was conducted. Patient age, gender, clinical details, provisional diagnosis, examination requested and referring clinician were recorded on a customised data sheet. Two radiologists independently evaluated the appropriateness of each request by comparing the clinical details and the provisional diagnosis provided with the 2012 American College of Radiology (ACR) guidelines for the appropriate use of MRI.Results: Four hundred and sixty-six patients (median age 42 years; interquartile range 19–55) who had 561 examinations were scheduled in the review period; 70 (15%) were children less than 6 years old. Neurosurgery (n = 164; 35%), orthopaedic (n = 144; 31%),neurology (n = 53; 11%) and paediatric (n = 27; 6%) outpatients accounted for the majority(81%) of referrals; 464 (99.6%) were from specialist clinics. MRIs of the spine (n = 314; 56%),brain (n = 152; 27%) and musculoskeletal system (n = 70, 13%) accounted for more than 95%of the investigations. In 455 cases (98%), the referral was congruent with published ACR guidelines for appropriate MRI utilisation.Conclusion: Scheduled outpatient MRI examinations at TBH reflect optimal clinical use of a limited resource. MRI utilisation is largely confined to traditional neuro-imaging. Any initiative to decrease the elective MRI waiting time should focus on service expansion.
Collapse
|
17
|
Olisemeke B, Chen YF, Hemming K, Girling A. The effectiveness of service delivery initiatives at improving patients' waiting times in clinical radiology departments: a systematic review. J Digit Imaging 2014; 27:751-78. [PMID: 24888629 PMCID: PMC4391068 DOI: 10.1007/s10278-014-9706-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
We reviewed the literature for the impact of service delivery initiatives (SDIs) on patients' waiting times within radiology departments. We searched MEDLINE, EMBASE, CINAHL, INSPEC and The Cochrane Library for relevant articles published between 1995 and February, 2013. The Cochrane EPOC risk of bias tool was used to assess the risk of bias on studies that met specified design criteria. Fifty-seven studies met the inclusion criteria. The types of SDI implemented included extended scope practice (ESP, three studies), quality management (12 studies), productivity-enhancing technologies (PETs, 29 studies), multiple interventions (11 studies), outsourcing and pay-for-performance (one study each). The uncontrolled pre- and post-intervention and the post-intervention designs were used in 54 (95%) of the studies. The reporting quality was poor: many of the studies did not test and/or report the statistical significance of their results. The studies were highly heterogeneous, therefore meta-analysis was inappropriate. The following type of SDIs showed promising results: extended scope practice; quality management methodologies including Six Sigma, Lean methodology, and continuous quality improvement; productivity-enhancing technologies including speech recognition reporting, teleradiology and computerised physician order entry systems. We have suggested improved study design and the mapping of the definitions of patient waiting times in radiology to generic timelines as a starting point for moving towards a situation where it becomes less restrictive to compare and/or pool the results of future studies in a meta-analysis.
Collapse
Affiliation(s)
- B Olisemeke
- Radiology Department, Heart of England NHS Foundation Trust, Birmingham, UK,
| | | | | | | |
Collapse
|