2022 ACR Quality and Safety Conference
Oct. 20–22, Washington, DC | In Person or Virtual
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Day 1 | Thursday, Oct. 20
1–3pm
Session 1 – (Available to in-person attendees only.)
- Point of Care Ultrasound (Room: Burnham) — Alex Towbin, MD, Jeannie Kwon, MD, Sonya Echols, MD, David Evans, MD, David Waldman, MD
- Value of Using RADS (Room: Latrobe) — Olga Brook, MD & Victoria Chernyak, MD
Break
3:30–5:30pm – (Available to in-person attendees only.)
Session 2
- Lessons Learned from the National Contrast Shortage: Are We Better Prepared for the Next Supply Chain Disruption? (Room: Burnham) — Pranay Krishnan, MD & Helise Coopersmith, MD
- Using the GRID Registry for QI and MIPS (Room: Latrobe) — Anh Duong, MD, Laurie Wadsworth, Vikki Casey, Wayne Wadsworth
Day 2 | Friday, Oct. 21
8:30–10am
Learning Breakfast/Roundtable (Room: Constitution CDE)
10–11:30am
High-Value Operational Improvement Strategies (Room: Constitution AB) — Moderators: Jay Pahade, MD & Shlomit Stein, MD
*The goal of this session is to present the user with ideas and frameworks to think about health care value and how locally led initiatives driven by radiologists can improve the care provided to patients.
- Introduction to the Q&S conference — Program Chairs
- Opening Keynote: Harmonizing the Drivers of Value-based Care Transformation: Professionalism, Provider-led Performance Improvement, Payers and Policy Makers — Pam Johnson, MD
- Making a Business Case for Equity in Healthcare and Imaging — Ruth Carlos, MD
- Operationalizing Quality Improvement: Implementing Solutions for ROI — Jay Pahade, MD
- Video Radiology Reports: A Tool to Improve Patient-Centered Radiology — Michael Recht, MD
- Panel Discussion
11:30–11:45am
Coffee Break
11:45am–1:05pm
Follow-Up Recommendations (Room: Constitution AB) — Moderator: Ben Wandtke, MD
*Incidental findings, often considered a nuisance, present an opportunity to identify cancers at their earliest and most treatable stage. Learn strategies to best identify incidental findings found on radiology exams, assure that appropriate high-quality recommendations are consistently being made and understand emerging data on the impact of recommendation follow-up tracking systems on the disparities in care. Tools to help you obtain resources or improve tracking systems will be provided.
- Measuring and Improving Recommendation Quality — Regan City, PA-C, CPHQ
- Optimizing Recommendation Identification — Woojin Kim, MD
- Measuring Return on Investment — Neville Irani, MD
- Impact of Follow-up Tracking on Disparities in Care — Chris Moore, MD
- Panel Discussion
- Scientific Abstracts:
- Improving Stroke CT Imaging Turnaround Time Through a Multidisciplinary Team Approach — Daniel Karolyi
- Improve Quality of Triphasic Abdominal CT Images — Kumlachew Abate
1:05–2:30pm
Lunch (Room: Constitution CDE)
2:30–4pm
Breakout Sessions (Note: These sessions will not be available to virtual attendees)
- Transitioning Peer Learning Into Quality Improvement (Room: Penn Quarter B) — Rich Sharpe, MD & Jenn Broder, MD
- Participating in a National Quality Improvement Learning Collaborative (Room: Declaration A) — David Larson, MD, Kandice Garcia Tomkins, MS, Kay Zacharias-Andrews, MBA, Chirag Parghi, MD, Melinda Willis, Erin Panter, Laurie Wadsworth, Ben Wandtke, MD, Neville Irani, MD
- Patient Experience in Operational Improvement (Room: Declaration B) — Arun Krishnaraj, MD & Nina Vincoff, MD
4–4:15pm
Coffee Break
4:15–5:30pm
Non-Interpretive AI (Room: Constitution AB) — Moderator: Matt Davenport, MD
*A mix of concise lectures and an interactive activity will teach participants how machine learning can be used to improve our practice outside image interpretation. This is a cross-disciplinary session by the Quality and Safty Commission and Informatics teams.
- The Impact of AI on Clinical Decision Support — Hanna Zafar, MD
- Using Data Science to Satisfy OPPE and FPPE Through Outcome Metrics — Atul Shinagare, MD
- Activity: How to Prioritize New AI Tools — Nabile Safdar, MD
- Using Data Science to Understand Radiology Access Disparities — Efren Flores, MD & Dania Daye, MD
5:30–7pm
Reception/Abstract Posters (Room: Grand Foyer)
Day 3 | Saturday, Oct. 22
Peer Learning (Room: Constitution AB) — Moderator: Jenn Broder, MD
- Current State of Peer Learning — Jenn Broder, MD
- Partnering with Leadership: How to Get Your C-Suite Onboard — Regan City, PA-C, CPHQ & Samir Patel, MD
- Translating Peer Learning Into Quality Improvement — Rich Sharpe, MD
- Opportunities Ahead: Envisioning the Future State of Peer Learning — Gloria Hwang, MD
- Panel Discussion
- Scientific Abstracts:
- ACR DIR in Digital Radiography: Developing Meaningful Reports for Quality Improvement — Xiang Li
- Optimizing Image Quality for Portable Chest and Abdomen Radiographs: A RITE Project — Ethan Larsen
11:05–11:15am
Coffee Break
11:15am–12:30pm
Lung Cancer Screening With Population Health (Room: Constitution AB) — Moderator: Ella Kazerooni, MD
*The goals of this session are to better understand why and how to improve lung cancer detection programs by reaching a diverse patient population and to use the ACR Lung Cancer Screening Registry data for quality improvement.
- Early Lung Cancer Detection: Reaching a More Diverse Population With Both Screening & Incidental Nodule Programs — Ella Kazerooni, MD
- Making the Business Case to Support Incidental Lung Nodule and Lung Cancer Screening Programs: LungPlan — Ella Kazerooni, MD
- Using Geospatial Analysis to Identify Gaps in Screening to Reach Diverse Populations: Lung Atlas — Liora Sahar, MD
- Using Your ACR Lung Cancer Screening Registry Data for Quality Improvement: New LCSR QI Templates — Shawn Teague, MD
- Panel Discussion
- Awards & Recognition/Closing Remarks
KEYNOTE SESSION: Challenges and Opportunities in Machine Reading of Radiology Exams
Machine learning methods are enabling computers to interpret unstructured document content and perform real-world tasks. Our keynote will highlight the latest trends in deep learning models that utilize imaging, free text, and structured data to advance early diagnosis, treatment, and disease prevention.
Speaker: Regina Barzilay, PhD, Professor, Department of Electrical Engineering and Computer Science and Member, Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (MIT)
SESSION 4: Current state of AI in Practice: Diverse Perspectives and Panel Discussion
Artificial intelligence in the health care industry is gaining traction. Hear from those with experience using AI in clinical care and hospital operations about the issues that will impact you most.
- Insight from the perspective of the radiologist, informatics/IT department, business leader and patient.
- How to begin using AI
- Looking for increased efficiency in operations and incorporating AI into workflows
Moderator: Amy Kotsenas, MD, ACR DSI Council Steering Committee Liaison and Associate Professor of Radiology at Mayo Clinic, Rochester
Presenters:
Melissa A. Davis, MD, MBA, Section Chief, Emergency Radiology, Yale University
Daniel Blezek, PhD, Associate Consultant, Department of Radiology, Mayo Clinic
David Andrews, Patient Advocate
Christoph Wald, MD, PhD, MBA, FACR, Chairman, Department of Radiology, Lahey Hospital & Medical Center, Professor of Radiology, Tufts University Medical School
Don't miss this year's conference!
Keynote
Regina Barzilay, MD, PhD
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Gold Sponsor Title
Silver Sponsor Title
Bronze Sponsor Title
The American College of Radiology is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
Physician Credit Designation Statement
The American College of Radiology designates this in-person activity for a maximum of 12.5 AMA PRA Category 1 Credit(s)™, and virtual activity for a maximum of 9.5 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Technologist Accreditation Statement
The American College of Radiology (ACR) is approved by the American Registry of Radiologic Technologists (ARRT) as a Recognized Continuing Education Evaluation Mechanism (RCEEM) to sponsor and/or review Continuing Education programs for Radiologic Technologists and Radiation Therapists.
Technologist Credit Designation Statement
The American College of Radiology designates this educational in-person activity as meeting the criteria for up to 12.75 Category A credit hour(s) and virtual activity up to 9.75 Category A credit hours of the ARRT.
SAM/SA-CME Accreditation Statement
This activity meets the American Board of Radiology’s (ABR) criteria for a self-assessment activity and is designated for up to 4 SAM/SA-CME credits toward the ABR’s Maintenance of Certification program.
Contact Information
For information about the accreditation of this program, please contact the ACR at [email protected].