The following post was contributed by William W. Boonn, MD, and David S. Hirschorn, MD, ACR 2016 — The Crossroads of Radiology® Informatics and Innovations Pathway Co-Chairs.
We live (and practice) in a time where health care and technology continue to advance rapidly. To keep up with – or at least not get run over by these changes – we as radiologists have to face some tough questions.
How do we radiologists maintain our edge as leaders in imaging informatics and in applying technological advances to practical medical use?
Do you know all you need to about advanced data science tools, clinical decision support and electronic medical records (EMR) optimization to help support enterprise imaging initiatives and adapt to new alternative payment models?
What can you and I do to secure our place in the evolving national health IT landscape?
Then there is another question. Today’s world of machine learning, deep learning and big data impacts life with innovations like self-driving cars, face recognition systems and interpretation of medical images. How will advanced data science tools impact the roles that radiologists, imaging informaticists and even the American College of Radiology (ACR) take to develop and use computers to help interpret medical images?
As radiology professionals, we must better understand new advances in health care technology and how these developments can help document quality-based care, to continue to demonstrate the value of our specialty.
Why not let American College of Radiology (ACR) help you?
The ACR is at the forefront of informatics and innovations, with tools and technical resources to help find common ground and reach common expectations. At ACR 2016 — The Crossroads of Radiology®, you can gain understanding of the practical use — and integration — of new information technology (IT) solutions.
To help you better understand new advances in health care technology, the ACR 2016 Informatics and Innovation Pathway will help participants make practical use of imaging informatics and new IT solutions. Attendees will review current challenges, learn how to successfully integrate new information technology and achieve positive outcomes.
- Machine Learning, Deep Learning, Big Data and Data Science in Radiology
- Quality and Productivity Metrics: Using Business Intelligence Tools and Data Mining Strategies to Demonstrate Value
- Implementing Clinical Decision Support: Opportunities and Challenges
- Actionable Findings and Communication: Challenges and Opportunities
- Image Exchange: Where We Are and Where We Are Going and Teleradiology — Challenges and Opportunities
- Optimizing Your Electronic Medical Record (EMR) and Mobile Technology
- Tools for Radiologists and Social Media
What do you think? Which of these topics will support you and your practice — and why?