radloop®

Why is poor follow-up for actionable findings such a major problem in radiology? 🔵 radloop®'s Matthew (Matt) Friedland recently had a conversation with the Director of Risk Management/Claims, Compliance, and Physician Recruiting at Lake Medical Imaging, Josh Floyd PhD, MSCM, CPHRM, about the landscape of actionable findings in radiology. Here is the first of more clips to come! 📹 ✅ This is an overview of the underappreciated problem of poor follow-up for actionable findings in radiology reports. Identifying a key finding is only the first step in a care coordination process that hopefully ends with appropriate and timely follow-up care. But as we all know, that does not always happen... Reference - prevalence of Incidental Findings in CT scans: https://lnkd.in/gRKzksUi Disclosure: Lake Medical Imaging is a radloop® client. #radiology #ai #nlp #actionablefindings #qualityofcare #patientcare #medicine #digitalhealth #legalcompliance

What factors may be associated with worse follow-up after 'probably benign' breast findings? (noncompleted BI-RADS 3 follow-up) A recent study from Harvard Medical School, Brigham and Women's Hospital, and Mass General Brigham tried to answer that question—they completed a retrospective analysis of almost 9,000 exams over one year (2021). Here is what they found: "Factors associated with incomplete follow-up included whether patients underwent ultrasound (odds ratio: 0.22), MRI (0.1), were of Asian race (0.77), under age 40 (0.22), single (0.68), divorced (0.77), widowed (0.61), on public insurance (0.84), or using self-pay (0.59). Orders that were placed greater than eight months after the index exam (0.2), made by a non-primary care provider (0.51), or not scheduled on the same day also were less likely to result in follow-up imaging. " 🔗 https://lnkd.in/g8Ge4S7J 📝 Paper: https://lnkd.in/ghZPm_DT Authors: Catherine Giess MD, Elyse Lynch,  Ronilda Lacson MD PhD, Pamela DiPiro MD, Fatima Salah MD, Stephanie H Chung MD, Gary X. Wang MD, and Ramin Khorasani MD

🎉 It's almost that time of year again! 🔵 The radloop® team is coming to #RSNA2024! Come meet us at Booth 7803 North Hall, Level 3. 📆 Book an appointment online at radloop.net/rsna !

🏥 Investigators at Kumamato University used an integrated, machine-learning platform to help determine which incidental findings require further investigation. AI and ML can help physicians triage the large pile of incidental findings that they encounter each day, and help us learn the characteristics of worrisome findings. 📝 Excerpt: '“While most [incidental imaging findings] are low-risk lesions, their clinical management is often challenging because they occasionally include high-risk lesions,” corresponding author Seitaro Oda MD, PhD, from the Department of Diagnostic Radiology at Kumamoto University, and co-authors explain. “In other words, additional interventions for IIFs can lead to overtreatment, while underestimation of IIFs can result in overlooking high-risk lesions, with serious implications for patient health.” To streamline the communication of IIFs at their institution, experts at Kumamoto University Hospital in Japan integrated a machine learning-based platform that alerts providers of incidental findings in their EMR.' 🔗 https://lnkd.in/gnukRVt4

The Centers for Disease Control and Prevention includes radiology in it's call to strive for diagnostic excellence. Radiologists are tasked with providing knowledge about the proper use of diagnostics and ensuring the appropriate interpretation and follow-up of imaging findings. 📝 Excerpt: "DxEx, as the CDC calls it for short, encompasses practices to improve this process, ensuring that imaging and other tests are ordered, interpreted, communicated and acted on appropriately.... Radiologists and other imaging staffers can serve as consultants to improve appropriate ordering, aid in interpreting results and optimize reporting to guide best practices. " Link 🔗: https://lnkd.in/gNjZPbgi

Shout out to radloop® for supplying the fuel for attendees across the outstanding sessions at American College of Radiology's #QSI2024

🙋♂️ How often have you seen incidental coronary calcium or lung nodules on a CT scan that is ordered for something else? 🤒 Following these findings plays a major role in diagnosing preclinical disease. 🤖 Using AI-based screenings for these findings is a great decision for both patient care and financial sustainability. 🗣️ "...opportunistic screening algorithms will likely offer health systems a new way to not only better serve patients by catching diseases earlier when they are easier to treat or prevent, but also serve as an entry point for additional testing and treatments without large amounts of time or investment to create new screening programs." - Radiology Business article by Dave Fornell https://lnkd.in/gMkDpyGY

Happy 4th of July from Radloop! 🇺🇸🎇🎆

Completing recommended cancer screenings is crucial to public health. Catching disease early can lead to early intervention and improved outcomes. This study from JAMA Network Open (written up in Health Imaging) investigated a multi-faceted electronic health record intervention for Lung Cancer Screening. The improvement in closing the gap on missing lung cancer screening for this study shows the potential for our better use of technology to improve patients' lives and help them complete their cancer screenings. Authors: Polina Kukhareva, PhD, MPH, FAMIA, Haojia Li MS, Tanner Caverly MD, MPH, et al. 🔗 Link: https://lnkd.in/gTmJFdJi

🔵 "Radiologists are at a clear disadvantage in Medicare's MIPS program." 🔵 As we've learned, there are not enough measures to allow radiologists to succeed in the Merit-Based Incentive Payment System (MIPS) as it currently exists. It is very difficult for radiologists to avoid a negative payment adjustment. This new paper highlights the need to expand radiology-specific measures. 📝 Excerpt from Harvey L. Neiman Health Policy Institute Paper: "In 2021, there were only 9 available MIPS measures for diagnostic radiology versus 65 in family medicine. Physicians in radiology-only practices scored “significantly lower” in MIPS when compared to others working in doc groups where rads were not the predominant specialty." 🔗 Link: https://lnkd.in/d9SeZxYd Paper Authors: YoonKyung Chung, PhD, Lauren Nicola, MD, Chi-Mei Liu, Ph.D., MBA, MA, Elizabeth Rula, PhD